feat: add search_entity_labels tool for fuzzy entity search

src/daniel_lightrag_mcp/__init__.py

@@ -56,6 +56,8 @@
     "RelationInfo",
     "GraphResponse",
     "LabelsResponse",
+    "EntitySearchResult",
+    "EntitySearchResponse",
     "EntityExistsResponse",
     "EntityUpdateResponse",
     "RelationUpdateResponse",

src/daniel_lightrag_mcp/client.py

@@ -17,7 +17,7 @@
     DeleteDocByIdResponse, ClearDocumentsResponse, PipelineStatusResponse, TrackStatusResponse,
     StatusCountsResponse, ClearCacheResponse, DeletionResult, QueryResponse, GraphResponse,
     LabelsResponse, EntityExistsResponse, EntityUpdateResponse, RelationUpdateResponse,
-    HealthResponse, TextDocument
+    HealthResponse, TextDocument, EntitySearchResponse, EntitySearchResult
 )
 
 
@@ -429,6 +429,16 @@ async def get_graph_labels(self) -> LabelsResponse:
             response_data = {"labels": response_data}
         return LabelsResponse(**response_data)
 
+    async def search_entity_labels(self, queries: List[str], limit: int = 10) -> EntitySearchResponse:
+        """Search for entity labels matching one or more query strings."""
+        results = []
+        for query in queries:
+            params = {"q": query, "limit": min(limit, 100)}
+            response_data = await self._make_request("GET", "/graph/label/search", params=params)
+            matches = response_data if isinstance(response_data, list) else []
+            results.append(EntitySearchResult(query=query, matches=matches))
+        return EntitySearchResponse(results=results)
+
     async def check_entity_exists(self, entity_name: str) -> EntityExistsResponse:
         """Check if an entity exists in the knowledge graph."""
         params = {"name": entity_name}

src/daniel_lightrag_mcp/models.py

@@ -315,6 +315,17 @@ class LabelsResponse(BaseModel):
     relation_labels: List[str] = Field(default_factory=list)
 
 
+class EntitySearchResult(BaseModel):
+    """Search results for a single query string."""
+    query: str = Field(..., description="The search query")
+    matches: List[str] = Field(default_factory=list, description="Matching entity labels")
+
+
+class EntitySearchResponse(BaseModel):
+    """Response model for entity label search (batch)."""
+    results: List[EntitySearchResult] = Field(default_factory=list)
+
+
 class EntityExistsResponse(BaseModel):
     """Response model for entity existence check."""
     exists: bool = Field(..., description="Whether entity exists")

src/daniel_lightrag_mcp/server.py

@@ -493,6 +493,26 @@ async def handle_list_tools() -> List[Tool]:#ListToolsResult:
                 "required": []
             }
         ),
+        Tool(
+            name="search_entity_labels",
+            description="Fuzzy-search entity labels in the knowledge graph. Accepts one or more query strings and returns matching entity names per query. Useful for checking whether a concept is indexed before querying, and for finding the canonical form of an entity name.",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "queries": {
+                        "type": "array",
+                        "items": {"type": "string"},
+                        "description": "One or more search terms"
+                    },
+                    "limit": {
+                        "type": "integer",
+                        "description": "Max results per query (default 10, max 100)",
+                        "default": 10
+                    }
+                },
+                "required": ["queries"]
+            }
+        ),
         Tool(
             name="check_entity_exists",
             description="Check if an entity exists in the knowledge graph",
@@ -1541,6 +1561,14 @@ async def handle_call_tool(self, request: CallToolRequest) -> dict:
                 logger.error(f"  - Full traceback: {traceback.format_exc()}")
                 raise
 
+        elif tool_name == "search_entity_labels":
+            queries = arguments.get("queries", [])
+            limit = arguments.get("limit", 10)
+            if not queries:
+                raise LightRAGValidationError("queries must be a non-empty list")
+            result = await lightrag_client.search_entity_labels(queries=queries, limit=limit)
+            return _create_success_response(result, tool_name)
+
         elif tool_name == "check_entity_exists":
             logger.info("EXECUTING CHECK_ENTITY_EXISTS TOOL:")
             logger.info(f"  - Tool: {tool_name}")