feat(mcp): add ragflow_list_datasets and ragflow_list_chats tools (#15384)

## Summary

Add two new MCP tools to the RAGFlow MCP server:

1. **ragflow_list_datasets** - List all accessible datasets with IDs,
names, descriptions
2. **ragflow_list_chats** - List all accessible chat assistants with
IDs, names, descriptions

### Implementation
- Added `list_chats()` method to `RAGFlowConnector`
- Registered both tools in `list_tools()` and `call_tool()`
- Follows existing `ragflow_retrieval` pattern for error handling

### Usage via langchain-mcp-adapters

---------

Co-authored-by: saltsalt123 <saltsalt123@users.noreply.github.com>
Co-authored-by: yzc <yuzhichang@gmail.com>

mcp/server/server.py

@@ -163,6 +163,33 @@ class RAGFlowConnector:
 
         return res_json
 
+    async def list_chats(self, *, api_key: str, page: int = 1, page_size: int = 30, orderby: str = "create_time", desc: bool = True):
+        """Return accessible chat assistants as newline-delimited JSON for MCP tool descriptions."""
+        logging.info("Listing chat assistants via MCP (page=%s, page_size=%s)", page, page_size)
+        params = {"page": page, "page_size": page_size, "orderby": orderby, "desc": json.dumps(desc)}
+        res = await self._get("/chats", params, api_key=api_key)
+        if not res or res.status_code != 200:
+            error_message = None
+            if res is not None:
+                try:
+                    error_message = res.json().get("message")
+                    logging.warning("list_chats request failed: status=%s message=%s", res.status_code, error_message)
+                except Exception:
+                    error_message = None
+                    logging.warning("list_chats request failed: status=%s (parse error)", res.status_code)
+            raise Exception([types.TextContent(type="text", text=error_message or "Cannot list chats.")])
+        res_json = res.json()
+        if res_json.get("code") != 0:
+            logging.warning("list_chats API error: code=%s message=%s", res_json.get("code"), res_json.get("message"))
+            raise Exception([types.TextContent(type="text", text=res_json.get("message", "Cannot list chats."))])
+        chat_count = len(res_json.get("data", []))
+        logging.info("list_chats returned %d chat(s)", chat_count)
+        result_list = []
+        for data in res_json.get("data", []):
+            d = {"id": data.get("id"), "name": data.get("name"), "description": data.get("description", "")}
+            result_list.append(json.dumps(d, ensure_ascii=False))
+        return "\n".join(result_list)
+
     async def _fetch_all_datasets(
         self,
         *,
@@ -506,6 +533,7 @@ def with_api_key(required: bool = True):
 @with_api_key(required=True)
 async def list_tools(*, connector: RAGFlowConnector, api_key: str) -> list[types.Tool]:
     dataset_description = await connector.list_datasets(api_key=api_key)
+    chat_description = await connector.list_chats(api_key=api_key)
 
     return [
         types.Tool(
@@ -570,6 +598,52 @@ async def list_tools(*, connector: RAGFlowConnector, api_key: str) -> list[types
                 "required": ["question"],
             },
         ),
+        types.Tool(
+            name="ragflow_list_datasets",
+            description="List all accessible datasets (knowledge bases) in RAGFlow. Returns dataset IDs, names, and descriptions. Use this tool to discover which datasets are available before performing retrieval."
+            + dataset_description,
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "page": {
+                        "type": "integer",
+                        "description": "Page number",
+                        "default": 1,
+                        "minimum": 1,
+                    },
+                    "page_size": {
+                        "type": "integer",
+                        "description": "Results per page",
+                        "default": 100,
+                        "minimum": 1,
+                        "maximum": 1000,
+                    },
+                },
+            },
+        ),
+        types.Tool(
+            name="ragflow_list_chats",
+            description="List all accessible chat assistants in RAGFlow. Returns chat assistant IDs, names, and descriptions. Use this tool to discover available chat assistants that can be used for conversations."
+            + chat_description,
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "page": {
+                        "type": "integer",
+                        "description": "Page number",
+                        "default": 1,
+                        "minimum": 1,
+                    },
+                    "page_size": {
+                        "type": "integer",
+                        "description": "Results per page",
+                        "default": 30,
+                        "minimum": 1,
+                        "maximum": 100,
+                    },
+                },
+            },
+        ),
     ]
 
 
@@ -609,6 +683,19 @@ async def call_tool(
             rerank_id=rerank_id,
             force_refresh=force_refresh,
         )
+
+    if name == "ragflow_list_datasets":
+        page = arguments.get("page", 1)
+        page_size = arguments.get("page_size", 100)
+        result = await connector.list_datasets(api_key=api_key, page=page, page_size=page_size)
+        return [types.TextContent(type="text", text=result)]
+
+    if name == "ragflow_list_chats":
+        page = arguments.get("page", 1)
+        page_size = arguments.get("page_size", 30)
+        result = await connector.list_chats(api_key=api_key, page=page, page_size=page_size)
+        return [types.TextContent(type="text", text=result)]
+
     raise ValueError(f"Tool not found: {name}")