Replace fastapi_mcp with the MCP Python SDK (FastMCP) to fix RecursionError on recursive Pydantic models, expose explicit @mcp.tool() handlers that call FeatureStore directly, and add registry discovery, data access, and materialization tools with flat LLM-friendly schemas.

Signed-off-by: Chaitany patel <patelchaitany93@gmail.com>
Rerun-CI: true

Author: patelchaitany

examples/agent_feature_store/agent.py

@@ -167,15 +167,12 @@ async def _discover_feast_tools() -> dict[str, str]:
 
 
 def _parse_online_features(data: dict) -> dict[str, Any]:
-    """Parse the response from get-online-features into a flat dict."""
-    results = data.get("results", [])
-    feature_names = data.get("metadata", {}).get("feature_names", [])
-    features: dict[str, Any] = {}
-    for i, name in enumerate(feature_names):
-        values = results[i].get("values", [])
-        val = values[0] if values else None
+    """Parse the MCP to_dict() response into a flat dict of first-row values."""
+    features = {}
+    for key, values in data.items():
+        val = values[0] if isinstance(values, list) and values else values
         if val is not None:
-            features[name] = val
+            features[key] = val
     return features
 
 
@@ -214,15 +211,14 @@ async def tool_search_knowledge_base(query: str) -> list[dict[str, Any]]:
             "api_version": 2,
         },
     )
-    results = data.get("results", [])
-    feature_names = data.get("metadata", {}).get("feature_names", [])
-
-    num_docs = len(results[0]["values"]) if results else 0
+    first_col = next(iter(data.values()), [])
+    num_docs = len(first_col) if isinstance(first_col, list) else 0
     docs = []
     for doc_idx in range(num_docs):
         doc = {}
-        for feat_idx, name in enumerate(feature_names):
-            doc[name] = results[feat_idx]["values"][doc_idx]
+        for key, values in data.items():
+            if isinstance(values, list) and doc_idx < len(values):
+                doc[key] = values[doc_idx]
         if doc.get("title"):
             docs.append(doc)
     return docs

sdk/python/feast/feature_server.py

@@ -353,8 +353,14 @@ async def lifespan(app: FastAPI):
 
         await store.initialize()
         async_refresh()
+
+        mcp_sm = getattr(app.state, "mcp_session_manager", None)
         try:
-            yield
+            if mcp_sm:
+                async with mcp_sm.run():
+                    yield
+            else:
+                yield
         finally:
             stop_refresh()
             if offline_batcher is not None:

sdk/python/feast/infra/mcp_servers/__init__.py

@@ -1,9 +1,10 @@
 # MCP (Model Context Protocol) server implementations for Feast
 
 from .mcp_config import McpFeatureServerConfig
-from .mcp_server import add_mcp_support_to_app
+from .mcp_server import add_mcp_support_to_app, create_mcp_server
 
 __all__ = [
     "McpFeatureServerConfig",
     "add_mcp_support_to_app",
+    "create_mcp_server",
 ]

sdk/python/feast/infra/mcp_servers/mcp_config.py

@@ -8,19 +8,16 @@
 class McpFeatureServerConfig(BaseFeatureServerConfig):
     """MCP (Model Context Protocol) Feature Server configuration."""
 
-    # Feature server type selector
     type: Literal["mcp"] = "mcp"
 
-    # Enable MCP server support - defaults to False as requested
     mcp_enabled: StrictBool = False
 
-    # MCP server name for identification
     mcp_server_name: StrictStr = "feast-mcp-server"
 
-    # MCP server version
     mcp_server_version: StrictStr = "1.0.0"
 
     mcp_transport: Literal["sse", "http"] = "sse"
 
-    # The endpoint definition for transformation_service (inherited from base)
+    mcp_base_path: StrictStr = "/mcp"
+
     transformation_service_endpoint: StrictStr = "localhost:6566"