diff --git a/backend/docs/CONFIGURATION.md b/backend/docs/CONFIGURATION.md
index 491f7b254..f011d11d5 100644
--- a/backend/docs/CONFIGURATION.md
+++ b/backend/docs/CONFIGURATION.md
@@ -279,6 +279,67 @@ container or Pod, not the host machine.
 This integration is retrieval-only. Dataset creation, uploads, parsing, and
 deletion remain in RAGFlow and are not exposed as Agent tools or DeerFlow APIs.
 
+### LightRAG Knowledge Retrieval
+
+LightRAG integration is disabled by default. It is an alternative provider for
+the same read-only `knowledge_search` tool: an operator picks RAGFlow or
+LightRAG by which entry appears in the `tools:` list — the two entries share
+one name, and on duplicate names DeerFlow keeps the **first** configured
+entry, so configure exactly one. Requires LightRAG v1.4.9 or newer: v1.4.8
+introduced the data-retrieval endpoint but returned a pre-envelope response
+shape, and the `status`/`data` envelope plus the citation fields consumed
+here shipped in v1.4.9. DeerFlow does not persist any index
+metadata; LightRAG stays the sole source of truth, and the deployment's
+single indexed workspace is always searched.
+
+```yaml
+tool_groups:
+  - name: knowledge
+
+tools:
+  - name: knowledge_search
+    group: knowledge
+    use: deerflow.community.lightrag.tools:knowledge_search_tool
+    base_url: http://localhost:9621
+    api_key: $LIGHTRAG_API_KEY
+    mode: mix
+    timeout: 30
+    top_k: 60
+    chunk_top_k: 8
+    max_chars_per_chunk: 800
+    max_total_chars: 8000
+```
+
+The tool is opt-in through the normal `tools:` list. Retrieval uses LightRAG's
+`POST /query/data` endpoint, which performs no LLM generation and returns
+structured entities, relationships, chunks, and references; DeerFlow keeps the
+chunks — the document text the selected mode already ranked as relevant — and
+formats them as citation-numbered text, dropping the graph objects to stay
+compact and keep the citation shape shared with the RAGFlow provider. `mode`
+selects the retrieval strategy (`naive`, `local`, `global`, `hybrid`, or
+`mix`; default `mix`, matching the LightRAG API's own `QueryRequest` default;
+`bypass` is rejected because it skips the index entirely). `top_k` bounds the
+entities retrieved in `local` mode or relationships in `global` mode, and the
+optional `chunk_top_k` bounds the text chunks retrieved and kept after
+reranking; both are capped at 1000 by the LightRAG server. Short queries that
+fail LightRAG's minimum-length validation surface the server's readable
+message. `max_chars_per_chunk` / `max_total_chars` bound the model-visible
+output size.
+
+`api_key` is optional because LightRAG may run without authentication. Only
+omit it for loopback or trusted-network deployments — a network-exposed
+LightRAG must have authentication enabled, and then the key is sent as the
+`X-API-Key` header and redacted from every model-visible error and from
+server logs. Blank values are treated as unauthenticated. `base_url` must not
+contain embedded username or password information, and for Docker or
+Kubernetes it must be reachable from the Gateway container or Pod.
+
+Internal identifiers (chunk IDs and the response-local reference IDs) are
+never exposed to the Agent; citations use the operator-readable `file_path`.
+This integration is retrieval-only. Document insertion, indexing, and graph
+mutation remain in LightRAG and are not exposed as Agent tools or DeerFlow
+APIs.
+
 ### Tool Groups
 
 Organize tools into logical groups:
diff --git a/backend/packages/harness/deerflow/community/lightrag/__init__.py b/backend/packages/harness/deerflow/community/lightrag/__init__.py
new file mode 100644
index 000000000..8b1378917
--- /dev/null
+++ b/backend/packages/harness/deerflow/community/lightrag/__init__.py
@@ -0,0 +1 @@
+
diff --git a/backend/packages/harness/deerflow/community/lightrag/client.py b/backend/packages/harness/deerflow/community/lightrag/client.py
new file mode 100644
index 000000000..9ad503401
--- /dev/null
+++ b/backend/packages/harness/deerflow/community/lightrag/client.py
@@ -0,0 +1,170 @@
+"""Minimal asynchronous client for the LightRAG APIs DeerFlow consumes."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import httpx
+
+QUERY_MODES = ("naive", "local", "global", "hybrid", "mix")
+
+
+class LightRAGError(Exception):
+    """Base class for normalized LightRAG failures."""
+
+
+class LightRAGAPIError(LightRAGError):
+    """LightRAG rejected the request with a readable failure."""
+
+
+class LightRAGConnectionError(LightRAGError):
+    """LightRAG could not be reached or timed out."""
+
+
+class LightRAGProtocolError(LightRAGError):
+    """LightRAG returned an invalid or unexpected HTTP response."""
+
+
+class LightRAGClient:
+    """Direct HTTP client for DeerFlow's read-only retrieval tools.
+
+    The client deliberately owns no cache or persistent state. A fresh HTTP
+    session is opened for each method call so callers do not need to manage a
+    client lifecycle. The optional API key is sent as the ``X-API-Key``
+    request header, the single credential form LightRAG documents for
+    API-key-authenticated servers; unauthenticated deployments simply omit it.
+    """
+
+    def __init__(
+        self,
+        *,
+        base_url: str,
+        api_key: str | None,
+        timeout: float = 30,
+        transport: httpx.AsyncBaseTransport | None = None,
+    ) -> None:
+        self.base_url = base_url.rstrip("/")
+        self.timeout = timeout
+        self._api_key = api_key
+        self._transport = transport
+
+    def _redact(self, value: object) -> str:
+        text = str(value)
+        if self._api_key:
+            text = text.replace(self._api_key, "[REDACTED]")
+        return text
+
+    def _error_message(self, payload: object, status_code: int) -> str | None:
+        """Extract a redacted, human-readable message from an error payload.
+
+        LightRAG failures carry text in ``message`` (QueryDataResponse
+        envelope) or ``detail`` (FastAPI error handler, either a string or a
+        list of validation objects whose ``msg`` holds the reason, prefixed by
+        pydantic's "Value error, "). Anything else — structured bodies, plain
+        text, missing payloads — yields ``None`` so the caller falls back to a
+        stable protocol error instead of dumping raw JSON at the model.
+        """
+        if not isinstance(payload, dict):
+            return None
+        candidate = payload.get("message")
+        if not isinstance(candidate, str) or not candidate.strip():
+            detail = payload.get("detail")
+            if isinstance(detail, str):
+                candidate = detail
+            elif isinstance(detail, list):
+                candidate = self._first_validation_message(detail)
+        if isinstance(candidate, str) and candidate.strip():
+            text = candidate.removeprefix("Value error, ").strip()
+            return self._redact(text)
+        return None
+
+    @staticmethod
+    def _first_validation_message(items: list[object]) -> str | None:
+        for item in items:
+            if isinstance(item, dict):
+                message = item.get("msg")
+                if isinstance(message, str) and message.strip():
+                    return message
+        return None
+
+    async def _request(self, method: str, path: str, *, json: dict[str, Any] | None = None) -> dict[str, Any]:
+        request_headers = {"Accept": "application/json"}
+        if self._api_key:
+            request_headers["X-API-Key"] = self._api_key
+        client_kwargs: dict[str, Any] = {
+            "base_url": self.base_url,
+            "headers": request_headers,
+            "timeout": self.timeout,
+        }
+        if self._transport is not None:
+            client_kwargs["transport"] = self._transport
+
+        try:
+            async with httpx.AsyncClient(**client_kwargs) as client:
+                response = await client.request(method, path, json=json)
+        except httpx.TimeoutException:
+            raise LightRAGConnectionError(f"LightRAG request timed out after {self.timeout:g} seconds.") from None
+        except httpx.RequestError as exc:
+            detail = self._redact(exc)
+            raise LightRAGConnectionError(f"{type(exc).__name__}: {detail}") from None
+
+        if response.is_error:
+            # A 404 on the data-retrieval endpoint means either a wrong
+            # base_url or a LightRAG older than v1.4.9, where /query/data did
+            # not exist yet; the default "Not Found" body helps neither case.
+            if response.status_code == 404:
+                raise LightRAGAPIError("LightRAG data-retrieval endpoint not found; check base_url or upgrade LightRAG to v1.4.9 or newer.")
+            try:
+                error_payload = response.json()
+            except ValueError:
+                raise LightRAGProtocolError(f"LightRAG request failed (HTTP {response.status_code}).") from None
+            message = self._error_message(error_payload, response.status_code)
+            if message is not None:
+                raise LightRAGAPIError(message)
+            raise LightRAGProtocolError(f"LightRAG request failed (HTTP {response.status_code}).")
+
+        try:
+            payload = response.json()
+        except ValueError:
+            raise LightRAGProtocolError("LightRAG returned invalid JSON.") from None
+        if not isinstance(payload, dict):
+            raise LightRAGProtocolError("LightRAG returned a non-object JSON payload.")
+
+        status = payload.get("status")
+        if status != "success":
+            if "chunks" in payload or "entities" in payload:
+                # v1.4.8 answers with a flat {entities, relationships,
+                # chunks, metadata} payload; the status/data envelope and the
+                # reference-bearing chunk fields both shipped in v1.4.9.
+                raise LightRAGAPIError("LightRAG server response predates v1.4.9; upgrade LightRAG to v1.4.9 or newer to use the data-retrieval endpoint.")
+            message = payload.get("message")
+            text = self._redact(message) if isinstance(message, str) and message.strip() else "LightRAG request failed."
+            raise LightRAGAPIError(text)
+        return payload
+
+    async def query_data(
+        self,
+        query: str,
+        *,
+        mode: str = "hybrid",
+        top_k: int = 60,
+        chunk_top_k: int | None = None,
+    ) -> dict[str, Any]:
+        """Run one read-only structured retrieval against ``POST /query/data``.
+
+        The data endpoint performs no LLM generation and always returns
+        entities, relationships, chunks, and references, which is exactly the
+        read-only shape DeerFlow's knowledge tool consumes.
+        """
+        if mode not in QUERY_MODES:
+            raise ValueError(f"mode must be one of {QUERY_MODES}")
+
+        request_body: dict[str, object] = {"query": query, "mode": mode, "top_k": top_k}
+        if chunk_top_k is not None:
+            request_body["chunk_top_k"] = chunk_top_k
+
+        payload = await self._request("POST", "/query/data", json=request_body)
+        data = payload.get("data")
+        if not isinstance(data, dict):
+            raise LightRAGProtocolError("LightRAG returned an invalid retrieval result.")
+        return data
diff --git a/backend/packages/harness/deerflow/community/lightrag/formatting.py b/backend/packages/harness/deerflow/community/lightrag/formatting.py
new file mode 100644
index 000000000..f6083074d
--- /dev/null
+++ b/backend/packages/harness/deerflow/community/lightrag/formatting.py
@@ -0,0 +1,89 @@
+"""Compact, citation-friendly formatting for LightRAG retrieval results."""
+
+from __future__ import annotations
+
+from collections.abc import Mapping
+from typing import Any
+
+
+def _truncate(value: str, max_chars: int, *, marker: str = "…") -> str:
+    if len(value) <= max_chars:
+        return value
+    if max_chars <= len(marker):
+        return marker[:max_chars]
+    return f"{value[: max_chars - len(marker)].rstrip()}{marker}"
+
+
+def _chunks(value: object) -> list[Mapping[str, Any]]:
+    if not isinstance(value, list):
+        return []
+    return [chunk for chunk in value if isinstance(chunk, Mapping)]
+
+
+def _reference_file_paths(value: object) -> dict[str, str]:
+    if not isinstance(value, list):
+        return {}
+    file_paths: dict[str, str] = {}
+    for reference in value:
+        if not isinstance(reference, Mapping):
+            continue
+        reference_id = reference.get("reference_id")
+        file_path = reference.get("file_path")
+        if isinstance(reference_id, str) and isinstance(file_path, str) and file_path.strip():
+            file_paths.setdefault(reference_id, file_path.strip())
+    return file_paths
+
+
+def format_retrieval_result(
+    result: Mapping[str, Any],
+    *,
+    max_chars_per_chunk: int = 800,
+    max_total_chars: int = 8000,
+) -> str:
+    """Format one LightRAG ``/query/data`` payload into compact cited text.
+
+    The consumed field names (``chunks[].content/file_path/chunk_id/reference_id``
+    and ``references[].reference_id/file_path``) are cross-checked against the
+    LightRAG v1.5.7 source tree; the endpoint shipped in v1.4.8 but only
+    v1.4.9 introduced the status/data envelope and these citation fields. Opaque
+    internal identifiers (``chunk_id`` and the response-local
+    ``reference_id``) are never emitted; the operator-readable ``file_path``
+    labels each citation instead. Entities and relationships are deliberately
+    dropped: the chunks are the document text the selected query mode already
+    ranked as relevant, and keeping the output compact preserves the citation
+    shape shared with the RAGFlow provider.
+    """
+    raw_chunks = _chunks(result.get("chunks"))
+    if not raw_chunks:
+        return "No relevant content found."
+
+    file_paths_by_reference = _reference_file_paths(result.get("references"))
+
+    entries: list[str] = []
+    matched_documents: list[str] = []
+    counts_by_document: dict[str, int] = {}
+    for index, chunk in enumerate(raw_chunks, start=1):
+        file_path = chunk.get("file_path")
+        if not isinstance(file_path, str) or not file_path.strip():
+            reference_id = chunk.get("reference_id")
+            file_path = file_paths_by_reference.get(str(reference_id)) if reference_id is not None else None
+        document_name = str(file_path).strip() if file_path and str(file_path).strip() else "Unknown document"
+
+        counts_by_document[document_name] = counts_by_document.get(document_name, 0) + 1
+        content = str(chunk.get("content") or "").strip()
+        content = _truncate(content, max_chars_per_chunk)
+        entries.append(f"[{index}] {document_name}\n{content}")
+
+    for document_name, count in counts_by_document.items():
+        unit = "chunk" if count == 1 else "chunks"
+        matched_documents.append(f"{document_name} ({count} {unit})")
+    entries.append(f"Matched documents: {', '.join(matched_documents)}")
+
+    formatted = "\n\n".join(entries)
+    truncation_marker = "… (response truncated)"
+    if len(formatted) <= max_total_chars:
+        return formatted
+    if max_total_chars <= len(truncation_marker):
+        return truncation_marker[:max_total_chars]
+    prefix_length = max_total_chars - len(truncation_marker)
+    return f"{formatted[:prefix_length].rstrip()}{truncation_marker}"
diff --git a/backend/packages/harness/deerflow/community/lightrag/tools.py b/backend/packages/harness/deerflow/community/lightrag/tools.py
new file mode 100644
index 000000000..ff2c23f53
--- /dev/null
+++ b/backend/packages/harness/deerflow/community/lightrag/tools.py
@@ -0,0 +1,164 @@
+"""Read-only Agent tool for operator-scoped LightRAG knowledge retrieval."""
+
+from __future__ import annotations
+
+import logging
+from collections.abc import Mapping
+from typing import Literal
+
+from langchain_core.tools import StructuredTool
+from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field, SecretStr, ValidationError, field_validator
+
+from deerflow.config import get_app_config
+
+from .client import LightRAGAPIError, LightRAGClient, LightRAGConnectionError, LightRAGProtocolError
+from .formatting import format_retrieval_result
+
+logger = logging.getLogger(__name__)
+
+_NO_RELEVANT_CONTENT = "No relevant content found."
+
+
+class _LightRAGRetrievalSettings(BaseModel):
+    """Validated provider settings stored on the knowledge_search tool entry."""
+
+    model_config = ConfigDict(validate_default=True)
+
+    base_url: AnyHttpUrl = Field(default="http://localhost:9621")
+    api_key: SecretStr | None = Field(default=None)
+    # LightRAG's QueryRequest also accepts "bypass", which skips the index and
+    # answers straight from the LLM; that would defeat a retrieval tool, so it
+    # is excluded on purpose. "mix" matches the LightRAG API's own default.
+    mode: Literal["naive", "local", "global", "hybrid", "mix"] = Field(default="mix")
+    timeout: float = Field(default=30, gt=0, le=600)
+    # The server caps both fields at MAX_QUERY_TOP_K = 1000; match that limit
+    # instead of inventing a tighter client-side one.
+    top_k: int = Field(default=60, ge=1, le=1000)
+    chunk_top_k: int | None = Field(default=None, ge=1, le=1000)
+    max_chars_per_chunk: int = Field(default=800, ge=1, le=100_000)
+    max_total_chars: int = Field(default=8000, ge=1, le=1_000_000)
+
+    @field_validator("base_url")
+    @classmethod
+    def _reject_url_userinfo(cls, value: AnyHttpUrl) -> AnyHttpUrl:
+        if value.username is not None or value.password is not None:
+            raise ValueError("base_url must not contain username or password information")
+        return value
+
+
+def _api_key(settings: _LightRAGRetrievalSettings) -> str | None:
+    # LightRAG may run without authentication, so a missing key stays valid;
+    # blank values are treated as unconfigured rather than rejected.
+    value = settings.api_key
+    if isinstance(value, SecretStr):
+        value = value.get_secret_value()
+    if isinstance(value, str) and value.strip():
+        return value.strip()
+    return None
+
+
+def _redact_api_key(value: object, api_key: str | None) -> str:
+    text = str(value)
+    if api_key:
+        text = text.replace(api_key, "[REDACTED]")
+    return text
+
+
+def _settings_from_extra(extra: Mapping[str, object]) -> _LightRAGRetrievalSettings:
+    return _LightRAGRetrievalSettings.model_validate(dict(extra))
+
+
+def _settings_or_error() -> tuple[_LightRAGRetrievalSettings | None, str | None]:
+    tool_config = get_app_config().get_tool_config("knowledge_search")
+    if tool_config is None:
+        return None, "Error: knowledge_search is not configured; add its LightRAG settings to the tools list in config.yaml."
+    try:
+        settings = _settings_from_extra(tool_config.model_extra or {})
+    except ValidationError:
+        logger.warning("LightRAG knowledge_search tool configuration is invalid")
+        return None, "Error: Invalid LightRAG settings for knowledge_search; check config.yaml."
+    return settings, None
+
+
+def _build_client(settings: _LightRAGRetrievalSettings) -> LightRAGClient:
+    return LightRAGClient(
+        base_url=str(settings.base_url).rstrip("/"),
+        api_key=_api_key(settings),
+        timeout=settings.timeout,
+    )
+
+
+def _tool_error(exc: Exception, settings: _LightRAGRetrievalSettings) -> str:
+    key = _api_key(settings)
+    safe_detail = _redact_api_key(exc, key)
+    base_url = _redact_api_key(str(settings.base_url).rstrip("/"), key)
+
+    if isinstance(exc, LightRAGAPIError):
+        logger.warning("LightRAG API rejected a read-only tool request: %s", safe_detail)
+        return f"Error: {safe_detail}"
+    if isinstance(exc, LightRAGConnectionError):
+        logger.warning("LightRAG connection failed for %s (%s)", base_url, type(exc).__name__)
+        return f"Error: Unable to connect to LightRAG ({base_url}): {safe_detail}"
+    if isinstance(exc, LightRAGProtocolError):
+        logger.warning("LightRAG returned an invalid response for a read-only tool request (%s)", type(exc).__name__)
+        return f"Error: LightRAG request failed: {safe_detail}"
+
+    logger.warning("Unexpected LightRAG read-only tool failure (%s)", type(exc).__name__)
+    return "Error: An unexpected LightRAG retrieval error occurred; try again later."
+
+
+async def knowledge_search(query: str) -> str:
+    """Search the operator-configured LightRAG instance.
+
+    LightRAG has no dataset catalog to scope: the deployment's single indexed
+    workspace is always searched with the configured retrieval mode, so no
+    binding resolution happens before the one read-only request.
+    """
+    query = query.strip()
+    if not query:
+        return "Error: query must not be empty."
+
+    settings, error = _settings_or_error()
+    if settings is None:
+        return error or "Error: Invalid LightRAG settings for knowledge_search; check config.yaml."
+
+    client = _build_client(settings)
+    try:
+        result = await client.query_data(
+            query,
+            mode=settings.mode,
+            top_k=settings.top_k,
+            chunk_top_k=settings.chunk_top_k,
+        )
+        formatted = format_retrieval_result(
+            result,
+            max_chars_per_chunk=settings.max_chars_per_chunk,
+            max_total_chars=settings.max_total_chars,
+        )
+        # API-key redaction remains mandatory on the success path; chunk and
+        # reference identifiers never enter the formatted text at all.
+        return _redact_api_key(formatted, _api_key(settings))
+    except Exception as exc:
+        return _tool_error(exc, settings)
+
+
+def _tool_description() -> str:
+    base = "Search the operator-approved LightRAG knowledge base and return compact, citation-numbered source chunks retrieved with the configured graph/vector mode."
+    return f"{base} Internal identifiers are never shown to the model."
+
+
+async def _knowledge_search_entrypoint(query: str) -> str:
+    """Search the operator-configured LightRAG knowledge base.
+
+    Args:
+        query: Specific question or search terms to retrieve from the configured private documents.
+    """
+    return await knowledge_search(query)
+
+
+knowledge_search_tool = StructuredTool.from_function(
+    coroutine=_knowledge_search_entrypoint,
+    name="knowledge_search",
+    description=_tool_description(),
+    parse_docstring=True,
+)
diff --git a/backend/tests/test_lightrag_client.py b/backend/tests/test_lightrag_client.py
new file mode 100644
index 000000000..6ebb6e923
--- /dev/null
+++ b/backend/tests/test_lightrag_client.py
@@ -0,0 +1,368 @@
+import json
+
+import httpx
+import pytest
+
+from deerflow.community.lightrag.client import (
+    LightRAGAPIError,
+    LightRAGClient,
+    LightRAGConnectionError,
+    LightRAGProtocolError,
+)
+
+
+@pytest.mark.anyio
+async def test_query_data_sends_documented_body_and_api_key_header() -> None:
+    requests: list[httpx.Request] = []
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        requests.append(request)
+        assert request.method == "POST"
+        assert request.url == httpx.URL("http://lightrag.test/query/data")
+        assert request.headers["X-API-Key"] == "lightrag-secret"
+        return httpx.Response(
+            200,
+            json={
+                "status": "success",
+                "message": None,
+                "data": {"chunks": [], "references": [], "entities": [], "relationships": []},
+            },
+        )
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test/",
+        api_key="lightrag-secret",
+        timeout=12,
+        transport=httpx.MockTransport(handler),
+    )
+
+    data = await client.query_data("annual leave", mode="hybrid", top_k=60)
+
+    assert data == {"chunks": [], "references": [], "entities": [], "relationships": []}
+    assert len(requests) == 1
+    assert json.loads(requests[0].content) == {"query": "annual leave", "mode": "hybrid", "top_k": 60}
+
+
+@pytest.mark.anyio
+async def test_query_data_omits_api_key_header_when_unauthenticated() -> None:
+    requests: list[httpx.Request] = []
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        requests.append(request)
+        assert "Authorization" not in request.headers
+        assert "X-API-Key" not in request.headers
+        return httpx.Response(200, json={"status": "success", "data": {"chunks": []}})
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key=None,
+        transport=httpx.MockTransport(handler),
+    )
+
+    await client.query_data("annual leave")
+
+    assert len(requests) == 1
+
+
+@pytest.mark.anyio
+async def test_query_data_sends_chunk_top_k_only_when_configured() -> None:
+    requests: list[httpx.Request] = []
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        requests.append(request)
+        return httpx.Response(200, json={"status": "success", "data": {"chunks": []}})
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    await client.query_data("annual leave", mode="mix", top_k=15, chunk_top_k=8)
+    await client.query_data("annual leave", mode="mix", top_k=15)
+
+    assert json.loads(requests[0].content) == {"query": "annual leave", "mode": "mix", "top_k": 15, "chunk_top_k": 8}
+    assert json.loads(requests[1].content) == {"query": "annual leave", "mode": "mix", "top_k": 15}
+
+
+@pytest.mark.anyio
+async def test_query_data_rejects_unknown_mode_before_request() -> None:
+    called = False
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        nonlocal called
+        called = True
+        return httpx.Response(500)
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(ValueError, match="mode must be one of"):
+        await client.query_data("fallback search", mode="vector")
+
+    assert called is False
+
+
+@pytest.mark.anyio
+async def test_non_success_envelope_is_normalized_and_redacts_api_key() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(
+            200,
+            json={"status": "failure", "message": "invalid credential lightrag-secret"},
+        )
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError) as exc_info:
+        await client.query_data("annual leave")
+
+    assert "invalid credential" in str(exc_info.value)
+    assert "lightrag-secret" not in str(exc_info.value)
+    assert "[REDACTED]" in str(exc_info.value)
+
+
+@pytest.mark.anyio
+async def test_http_error_envelope_message_is_used() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(
+            400,
+            json={"status": "failure", "message": "RAG query is too short"},
+        )
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError, match="RAG query is too short"):
+        await client.query_data("ab")
+
+
+@pytest.mark.anyio
+async def test_http_error_detail_string_is_used() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(401, json={"detail": "Invalid API key provided"})
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError, match="Invalid API key provided"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+async def test_structured_validation_error_message_is_extracted_from_detail() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(
+            422,
+            json={
+                "detail": [
+                    {
+                        "type": "value_error",
+                        "loc": ["body", "query"],
+                        "msg": "Value error, RAG query is too short. Enter at least 3 English characters or an equivalent combination where each Chinese, Japanese or Korean character counts as 2.",
+                    }
+                ]
+            },
+        )
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError) as exc_info:
+        await client.query_data("ab")
+
+    assert "RAG query is too short" in str(exc_info.value)
+    assert "Value error," not in str(exc_info.value)
+
+
+@pytest.mark.anyio
+async def test_structured_validation_error_without_readable_msg_falls_back_to_protocol_error() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(422, json={"detail": [{"type": "missing", "loc": ["body"]}]})
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGProtocolError, match=r"LightRAG request failed \(HTTP 422\)"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+@pytest.mark.parametrize("body", [None, '{"detail": "Not Found"}'])
+async def test_404_returns_upgrade_guidance_instead_of_plain_not_found(body: str | None) -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(404, text=body, headers={"Content-Type": "application/json"} if body else None)
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError, match="v1.4.9"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+async def test_pre_v149_flat_success_payload_returns_upgrade_error() -> None:
+    """v1.4.8 answers 200 with a flat payload (no status/data envelope).
+
+    Pinning this shape matters: the documented minimum is v1.4.9, so a v1.4.8
+    server must fail with explicit upgrade guidance instead of a generic
+    "request failed" that hides the version incompatibility.
+    """
+
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(
+            200,
+            json={
+                "entities": [{"entity_name": "LightRAG"}],
+                "relationships": [],
+                "chunks": [{"content": "v1.4.8 chunk without citation fields."}],
+                "metadata": {"query_mode": "hybrid"},
+            },
+        )
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError, match="predates v1.4.9"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+async def test_http_error_text_body_cannot_echo_api_key() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(500, text="internal error: lightrag-secret")
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGProtocolError) as exc_info:
+        await client.query_data("annual leave")
+
+    assert str(exc_info.value) == "LightRAG request failed (HTTP 500)."
+    assert "lightrag-secret" not in str(exc_info.value)
+
+
+@pytest.mark.anyio
+async def test_server_500_detail_string_is_used_verbatim() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(500, json={"detail": "Internal server error"})
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGAPIError, match="^Internal server error$"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+async def test_timeout_is_english_and_does_not_leak_api_key(caplog: pytest.LogCaptureFixture) -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        raise httpx.ReadTimeout("timed out with lightrag-secret", request=request)
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        timeout=2,
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGConnectionError) as exc_info:
+        await client.query_data("annual leave")
+
+    assert str(exc_info.value) == "LightRAG request timed out after 2 seconds."
+    assert "lightrag-secret" not in str(exc_info.value)
+    assert "lightrag-secret" not in caplog.text
+
+
+@pytest.mark.anyio
+async def test_request_error_is_normalized_and_redacts_api_key() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        raise httpx.ConnectError("refused with lightrag-secret", request=request)
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGConnectionError) as exc_info:
+        await client.query_data("annual leave")
+
+    assert "ConnectError" in str(exc_info.value)
+    assert "lightrag-secret" not in str(exc_info.value)
+    assert "[REDACTED]" in str(exc_info.value)
+
+
+@pytest.mark.anyio
+async def test_invalid_json_response_is_normalized_in_english() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(200, text="not-json")
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGProtocolError, match="LightRAG returned invalid JSON"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+async def test_non_object_json_payload_is_rejected() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(200, json=["not", "an", "object"])
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGProtocolError, match="non-object JSON payload"):
+        await client.query_data("annual leave")
+
+
+@pytest.mark.anyio
+async def test_non_dict_data_payload_is_rejected() -> None:
+    async def handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(200, json={"status": "success", "data": ["not-a-dict"]})
+
+    client = LightRAGClient(
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        transport=httpx.MockTransport(handler),
+    )
+
+    with pytest.raises(LightRAGProtocolError, match="invalid retrieval result"):
+        await client.query_data("annual leave")
diff --git a/backend/tests/test_lightrag_tools.py b/backend/tests/test_lightrag_tools.py
new file mode 100644
index 000000000..ac3ceda2e
--- /dev/null
+++ b/backend/tests/test_lightrag_tools.py
@@ -0,0 +1,419 @@
+import logging
+from pathlib import Path
+from types import SimpleNamespace
+from typing import Any
+
+import pytest
+
+import deerflow.community.lightrag.tools as lightrag_tools
+from deerflow.community.lightrag.client import LightRAGAPIError, LightRAGConnectionError
+from deerflow.community.lightrag.formatting import format_retrieval_result
+from deerflow.config.tool_config import ToolConfig
+from deerflow.tools.tools import get_available_tools
+
+CHUNK_ID = "71a4613a-e91b-4d3b-bdff-6f45d9ac1f80"
+
+
+def _data(
+    *,
+    chunks: list[dict[str, Any]] | None = None,
+    references: list[dict[str, Any]] | None = None,
+) -> dict[str, Any]:
+    return {
+        "chunks": chunks if chunks is not None else [],
+        "references": references if references is not None else [],
+        "entities": [],
+        "relationships": [],
+    }
+
+
+class FakeLightRAGClient:
+    def __init__(self, *, data: dict | None = None, error: Exception | None = None) -> None:
+        self.data = data if data is not None else _data()
+        self.error = error
+        self.query_calls: list[tuple[str, dict]] = []
+
+    async def query_data(self, query: str, **kwargs: object) -> dict:
+        if self.error is not None:
+            raise self.error
+        self.query_calls.append((query, kwargs))
+        return self.data
+
+
+def _config(
+    *,
+    configured: bool = True,
+    api_key: str | None = "lightrag-secret",
+    base_url: str = "http://lightrag.test",
+    mode: str = "mix",
+    extra: dict[str, object] | None = None,
+) -> SimpleNamespace:
+    settings: dict[str, object] = {
+        "base_url": base_url,
+        "api_key": api_key,
+        "mode": mode,
+        "timeout": 30,
+        "top_k": 60,
+        "max_chars_per_chunk": 800,
+        "max_total_chars": 8000,
+    }
+    settings.update(extra or {})
+    search_config = ToolConfig(
+        name="knowledge_search",
+        group="knowledge",
+        use="deerflow.community.lightrag.tools:knowledge_search_tool",
+        **settings,
+    )
+    return SimpleNamespace(
+        get_tool_config=lambda name: search_config if configured and name == "knowledge_search" else None,
+    )
+
+
+def _install(monkeypatch: pytest.MonkeyPatch, fake: FakeLightRAGClient, *, config: SimpleNamespace | None = None) -> None:
+    monkeypatch.setattr(lightrag_tools, "get_app_config", lambda: config or _config())
+    monkeypatch.setattr(lightrag_tools, "_build_client", lambda settings: fake)
+
+
+@pytest.mark.anyio
+async def test_knowledge_search_formats_citation_numbered_chunks(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient(
+        data=_data(
+            chunks=[
+                {
+                    "content": "Annual leave is based on years of service.",
+                    "file_path": "documents/handbook.md",
+                    "chunk_id": CHUNK_ID,
+                    "reference_id": "3",
+                },
+                {
+                    "content": "Sick leave requires a medical certificate.",
+                    "file_path": "documents/handbook.md",
+                    "chunk_id": "71a4613a-e91b-4d3b-bdff-6f45d9ac1f81",
+                    "reference_id": "3",
+                },
+            ],
+            references=[{"reference_id": "3", "file_path": "documents/handbook.md"}],
+        )
+    )
+    _install(monkeypatch, fake)
+
+    result = await lightrag_tools.knowledge_search("annual leave")
+
+    assert fake.query_calls == [("annual leave", {"mode": "mix", "top_k": 60, "chunk_top_k": None})]
+    assert "[1] documents/handbook.md\nAnnual leave is based on years of service." in result
+    assert "[2] documents/handbook.md\nSick leave requires a medical certificate." in result
+    assert "Matched documents: documents/handbook.md (2 chunks)" in result
+    assert CHUNK_ID not in result
+
+
+@pytest.mark.anyio
+async def test_knowledge_search_resolves_missing_chunk_file_path_from_references(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient(
+        data=_data(
+            chunks=[{"content": "Graph-reconstructed context.", "chunk_id": CHUNK_ID, "reference_id": "7"}],
+            references=[{"reference_id": "7", "file_path": "documents/graph-notes.md"}],
+        )
+    )
+    _install(monkeypatch, fake)
+
+    result = await lightrag_tools.knowledge_search("graph")
+
+    assert "[1] documents/graph-notes.md\nGraph-reconstructed context." in result
+    assert "Unknown document" not in result
+
+
+@pytest.mark.anyio
+async def test_knowledge_search_sends_configured_retrieval_settings(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient(data=_data(chunks=[{"content": "Guide.", "file_path": "docs/guide.md"}]))
+    _install(monkeypatch, fake, config=_config(mode="local", extra={"top_k": 12, "chunk_top_k": 6}))
+
+    result = await lightrag_tools.knowledge_search("guide")
+
+    assert fake.query_calls == [("guide", {"mode": "local", "top_k": 12, "chunk_top_k": 6})]
+    assert "Guide." in result
+
+
+@pytest.mark.anyio
+async def test_knowledge_search_works_without_api_key_for_unauthenticated_servers(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    fake = FakeLightRAGClient(data=_data(chunks=[{"content": "Open knowledge.", "file_path": "docs/open.md"}]))
+    _install(monkeypatch, fake, config=_config(api_key=None))
+
+    result = await lightrag_tools.knowledge_search("open")
+
+    assert "Open knowledge." in result
+    assert fake.query_calls
+
+
+@pytest.mark.anyio
+async def test_blank_api_key_is_treated_as_unauthenticated(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient(data=_data(chunks=[{"content": "Open knowledge.", "file_path": "docs/open.md"}]))
+    _install(monkeypatch, fake, config=_config(api_key="   "))
+
+    result = await lightrag_tools.knowledge_search("open")
+
+    assert "Open knowledge." in result
+    assert fake.query_calls
+
+
+@pytest.mark.anyio
+async def test_missing_knowledge_search_config_returns_english_guidance(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient()
+    _install(monkeypatch, fake, config=_config(configured=False))
+
+    result = await lightrag_tools.knowledge_search("leave")
+
+    assert result == "Error: knowledge_search is not configured; add its LightRAG settings to the tools list in config.yaml."
+    assert fake.query_calls == []
+
+
+@pytest.mark.anyio
+async def test_invalid_settings_return_english_guidance_without_leaking_values(
+    monkeypatch: pytest.MonkeyPatch,
+    caplog: pytest.LogCaptureFixture,
+) -> None:
+    fake = FakeLightRAGClient()
+    _install(monkeypatch, fake, config=_config(mode="vector"))
+
+    with caplog.at_level(logging.WARNING, logger="deerflow.community.lightrag.tools"):
+        result = await lightrag_tools.knowledge_search("leave")
+
+    assert result == "Error: Invalid LightRAG settings for knowledge_search; check config.yaml."
+    assert "vector" not in caplog.text
+    assert fake.query_calls == []
+
+
+@pytest.mark.anyio
+@pytest.mark.parametrize(
+    "base_url",
+    [
+        "http://lightrag-secret@lightrag.test",
+        "http://lightrag%2Dsecret@lightrag.test",
+        "http://user:lightrag-secret@lightrag.test",
+    ],
+)
+async def test_base_url_with_plain_or_encoded_userinfo_is_rejected_without_leaking_credentials(
+    monkeypatch: pytest.MonkeyPatch,
+    caplog: pytest.LogCaptureFixture,
+    base_url: str,
+) -> None:
+    fake = FakeLightRAGClient()
+    _install(monkeypatch, fake, config=_config(base_url=base_url))
+
+    with caplog.at_level(logging.WARNING, logger="deerflow.community.lightrag.tools"):
+        result = await lightrag_tools.knowledge_search("leave")
+
+    assert result == "Error: Invalid LightRAG settings for knowledge_search; check config.yaml."
+    assert "lightrag-secret" not in result
+    assert "lightrag-secret" not in caplog.text
+    assert "lightrag%2Dsecret" not in caplog.text
+    assert fake.query_calls == []
+
+
+@pytest.mark.anyio
+async def test_empty_query_has_english_error(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient()
+    _install(monkeypatch, fake)
+
+    result = await lightrag_tools.knowledge_search("   ")
+
+    assert result == "Error: query must not be empty."
+    assert fake.query_calls == []
+
+
+@pytest.mark.anyio
+async def test_empty_retrieval_has_explicit_english_message(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient()
+    _install(monkeypatch, fake)
+
+    result = await lightrag_tools.knowledge_search("nothing")
+
+    assert result == "No relevant content found."
+
+
+@pytest.mark.anyio
+async def test_api_error_is_returned_as_readable_text_and_logged(
+    monkeypatch: pytest.MonkeyPatch,
+    caplog: pytest.LogCaptureFixture,
+) -> None:
+    fake = FakeLightRAGClient(error=LightRAGAPIError("RAG query is too short"))
+    _install(monkeypatch, fake)
+
+    with caplog.at_level(logging.WARNING, logger="deerflow.community.lightrag.tools"):
+        result = await lightrag_tools.knowledge_search("ab")
+
+    assert result == "Error: RAG query is too short"
+    assert "too short" in caplog.text
+
+
+@pytest.mark.anyio
+async def test_connection_error_is_english_and_does_not_leak_key(
+    monkeypatch: pytest.MonkeyPatch,
+    caplog: pytest.LogCaptureFixture,
+) -> None:
+    fake = FakeLightRAGClient(error=LightRAGConnectionError("ConnectError: refused lightrag-secret"))
+    _install(monkeypatch, fake)
+
+    with caplog.at_level(logging.WARNING, logger="deerflow.community.lightrag.tools"):
+        result = await lightrag_tools.knowledge_search("leave")
+
+    assert result == "Error: Unable to connect to LightRAG (http://lightrag.test): ConnectError: refused [REDACTED]"
+    assert "lightrag-secret" not in result
+    assert "lightrag-secret" not in caplog.text
+
+
+@pytest.mark.anyio
+async def test_success_path_still_redacts_api_key(monkeypatch: pytest.MonkeyPatch) -> None:
+    fake = FakeLightRAGClient(data=_data(chunks=[{"content": "Accidental echo: lightrag-secret", "file_path": "docs/secret.md"}]))
+    _install(monkeypatch, fake)
+
+    result = await lightrag_tools.knowledge_search("secret")
+
+    assert "lightrag-secret" not in result
+    assert "[REDACTED]" in result
+
+
+def test_formatting_uses_only_documented_chunk_fields() -> None:
+    result = format_retrieval_result(
+        {
+            "chunks": [
+                {
+                    "content": "abcdefghij",
+                    "file_path": "docs/policy.md",
+                    "chunk_id": CHUNK_ID,
+                    "reference_id": "1",
+                    "unexpected_future_field": "ignored",
+                }
+            ],
+            "references": [{"reference_id": "1", "file_path": "docs/policy.md"}],
+        },
+        max_chars_per_chunk=5,
+        max_total_chars=1000,
+    )
+
+    assert "[1] docs/policy.md" in result
+    assert "abcd…" in result
+    assert "abcdefghij" not in result
+    assert CHUNK_ID not in result
+
+
+def test_formatting_without_chunk_file_path_or_reference_labels_unknown_document() -> None:
+    result = format_retrieval_result({"chunks": [{"content": "Orphan chunk.", "chunk_id": CHUNK_ID}]})
+
+    assert "[1] Unknown document\nOrphan chunk." in result
+    assert CHUNK_ID not in result
+
+
+def test_formatting_applies_total_response_truncation_in_english() -> None:
+    result = format_retrieval_result(
+        {"chunks": [{"content": "content " * 20, "file_path": f"documents/document-{index}.md"} for index in range(4)]},
+        max_chars_per_chunk=100,
+        max_total_chars=120,
+    )
+
+    assert len(result) <= 120
+    assert result.endswith("… (response truncated)")
+
+
+def test_retrieval_settings_load_provider_fields_and_hide_secret(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(lightrag_tools, "get_app_config", lambda: _config(mode="mix", extra={"top_k": 12, "chunk_top_k": 6}))
+
+    config, error = lightrag_tools._settings_or_error()
+
+    assert error is None
+    assert config is not None
+    assert str(config.base_url).rstrip("/") == "http://lightrag.test"
+    assert config.mode == "mix"
+    assert config.top_k == 12
+    assert config.chunk_top_k == 6
+    assert config.max_chars_per_chunk == 800
+    assert config.max_total_chars == 8000
+    assert "lightrag-secret" not in repr(config)
+
+
+def test_retrieval_settings_allow_omitting_api_key(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(lightrag_tools, "get_app_config", lambda: _config(api_key=None))
+
+    config, error = lightrag_tools._settings_or_error()
+
+    assert error is None
+    assert config is not None
+    assert config.api_key is None
+
+
+def test_agent_exposes_only_query_on_single_search_tool() -> None:
+    assert not hasattr(lightrag_tools, "list_knowledge_bases_tool")
+    assert not hasattr(lightrag_tools, "list_knowledge_bases")
+    assert lightrag_tools.knowledge_search_tool.name == "knowledge_search"
+    assert lightrag_tools.knowledge_search_tool.coroutine is not None
+    assert set(lightrag_tools.knowledge_search_tool.tool_call_schema.model_fields) == {"query"}
+
+
+def test_tool_assembly_hides_credentials_without_network_io(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(lightrag_tools, "_build_client", lambda settings: pytest.fail("tool assembly must not perform network IO"))
+    tool_config = ToolConfig(
+        name="knowledge_search",
+        group="knowledge",
+        use="deerflow.community.lightrag.tools:knowledge_search_tool",
+        base_url="http://lightrag.test",
+        api_key="lightrag-secret",
+        mode="hybrid",
+    )
+    config = SimpleNamespace(
+        tools=[tool_config],
+        sandbox=SimpleNamespace(use="example.remote:Sandbox"),
+        skill_evolution=SimpleNamespace(enabled=False),
+        models=[],
+        acp_agents={},
+        get_model_config=lambda name: None,
+    )
+
+    tools = get_available_tools(include_mcp=False, app_config=config)
+    assembled = next(tool for tool in tools if tool.name == "knowledge_search")
+
+    assert "LightRAG" in assembled.description
+    assert "lightrag-secret" not in assembled.description
+    assert {tool.name for tool in tools}.isdisjoint({"list_knowledge_bases"})
+
+
+def test_retrieval_settings_default_mode_matches_lightrag_request_default(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(lightrag_tools, "get_app_config", lambda: _config(mode="mix"))
+
+    config, error = lightrag_tools._settings_or_error()
+
+    assert error is None
+    assert config is not None
+    assert config.mode == "mix"
+
+
+def test_shared_knowledge_search_name_keeps_first_configured_entry() -> None:
+    """RAGFlow and LightRAG share the ``knowledge_search`` tool name.
+
+    This pins the config-layer behavior for that shared name so an operator
+    accidentally configuring both entries gets a documented outcome (the
+    first entry wins) instead of silent provider swapping.
+    """
+    from deerflow.config.app_config import AppConfig
+    from deerflow.config.sandbox_config import SandboxConfig
+
+    ragflow_entry = ToolConfig(
+        name="knowledge_search",
+        group="knowledge",
+        use="deerflow.community.ragflow.tools:knowledge_search_tool",
+    )
+    lightrag_entry = ToolConfig(
+        name="knowledge_search",
+        group="knowledge",
+        use="deerflow.community.lightrag.tools:knowledge_search_tool",
+    )
+
+    config = AppConfig(tools=[ragflow_entry, lightrag_entry], sandbox=SandboxConfig(use="example.remote:Sandbox"))
+
+    assert config.get_tool_config("knowledge_search") is ragflow_entry
+
+
+def test_lightrag_package_has_explicit_init_file() -> None:
+    package_dir = Path(lightrag_tools.__file__).resolve().parent
+
+    assert (package_dir / "__init__.py").is_file()
diff --git a/config.example.yaml b/config.example.yaml
index 2ffd807dc..7f8fb5d81 100644
--- a/config.example.yaml
+++ b/config.example.yaml
@@ -746,6 +746,28 @@ tools:
   #   max_chars_per_chunk: 800
   #   max_total_chars: 8000
 
+  # LightRAG knowledge retrieval (read-only). Alternative provider for the same
+  # knowledge_search tool; uncomment this entry instead of the RAGFlow one —
+  # duplicate names keep the first entry, so configure exactly one. Requires
+  # LightRAG v1.4.9+ (response envelope and citation fields). Searches the deployment's
+  # single indexed workspace through the data retrieval endpoint (no LLM
+  # generation inside LightRAG). `api_key` is optional; only omit it for
+  # loopback/trusted-network servers — when auth is enabled the key is sent as
+  # the X-API-Key header. `mode` picks the retrieval strategy: naive, local,
+  # global, hybrid, or mix (default mix, matching LightRAG's own default).
+  # Internal chunk and reference identifiers never reach the model.
+  # - name: knowledge_search
+  #   group: knowledge
+  #   use: deerflow.community.lightrag.tools:knowledge_search_tool
+  #   base_url: http://localhost:9621  # Docker: use a backend-reachable URL
+  #   api_key: $LIGHTRAG_API_KEY  # Omit only for unauthenticated trusted servers
+  #   mode: mix
+  #   timeout: 30
+  #   top_k: 60
+  #   chunk_top_k: 8  # Optional; omit to use the server default
+  #   max_chars_per_chunk: 800
+  #   max_total_chars: 8000
+
   # Web search tool (uses DuckDuckGo, no API key required)
   - name: web_search
     group: web
diff --git a/deploy/helm/deer-flow/values.yaml b/deploy/helm/deer-flow/values.yaml
index 3b214ff10..c42a79cfc 100644
--- a/deploy/helm/deer-flow/values.yaml
+++ b/deploy/helm/deer-flow/values.yaml
@@ -337,6 +337,25 @@ config: |
     #   top_k: 256
     #   max_chars_per_chunk: 800
     #   max_total_chars: 8000
+    # Optional tenant-shared, read-only LightRAG retrieval; alternative
+    # provider for the same knowledge_search tool (duplicate names keep the
+    # first entry, so configure exactly one). Requires LightRAG v1.4.9+. Put
+    # LIGHTRAG_API_KEY in `secrets` when the server enables API-key auth;
+    # omit `api_key` only for unauthenticated trusted-network deployments.
+    # Searches the single indexed workspace through the data-retrieval
+    # endpoint with no LLM generation inside LightRAG. Internal chunk and
+    # reference identifiers stay hidden from the Agent.
+    # - name: knowledge_search
+    #   group: knowledge
+    #   use: deerflow.community.lightrag.tools:knowledge_search_tool
+    #   base_url: http://lightrag:9621
+    #   api_key: $LIGHTRAG_API_KEY
+    #   mode: mix
+    #   timeout: 30
+    #   top_k: 60
+    #   chunk_top_k: 8  # Optional; omit to use the server default
+    #   max_chars_per_chunk: 800
+    #   max_total_chars: 8000
     - name: web_search
       group: web
       use: deerflow.community.ddg_search.tools:web_search_tool