feat: add lightrag-mcp MCP server + agent tooling

- Add AGENTS.md with repo guidelines
- Add lightrag-mcp: FastMCP server exposing insert_documents() + query_documents()
  to LLM agents via stdio transport, talks to LightRAG REST API
- Add scripts/patch-vllm-cpu.py for CPU inference patching
- Add .env.vllm for vLLM configuration
- Update flake.nix with expanded dev shell
- Update .env.lightrag
- Remove CLAUDE.md (replaced by AGENTS.md)

lightrag-mcp/main.py

@@ -0,0 +1,57 @@
+import os
+import httpx
+from fastmcp import FastMCP
+
+LIGHTRAG_URL = os.getenv("LIGHTRAG_URL", "http://localhost:9621")
+
+mcp = FastMCP("LightRAG")
+
+
+@mcp.tool
+async def insert_documents(documents: list[str]) -> str:
+    """Insert text documents into LightRAG for indexing.
+
+    Args:
+        documents: List of document strings to index. Each string is treated as a separate document.
+
+    Returns:
+        Tracking ID for the insertion operation.
+    """
+    async with httpx.AsyncClient(timeout=120.0) as client:
+        r = await client.post(
+            f"{LIGHTRAG_URL}/documents/texts",
+            json={"texts": documents},
+        )
+        r.raise_for_status()
+        data = r.json()
+        return data.get("track_id", data.get("message", "unknown"))
+
+
+@mcp.tool
+async def query_documents(query: str, mode: str = "mix", top_k: int = 60) -> dict:
+    """Query LightRAG and retrieve relevant context without LLM generation.
+
+    Args:
+        query: The search query string.
+        mode: Retrieval mode - "local", "global", "hybrid", "naive", "mix" (default: "mix").
+        top_k: Number of top results to retrieve (default: 60).
+
+    Returns:
+        Structured retrieval data including entities, relationships, and text chunks.
+    """
+    async with httpx.AsyncClient(timeout=120.0) as client:
+        r = await client.post(
+            f"{LIGHTRAG_URL}/query/data",
+            json={
+                "query": query,
+                "mode": mode,
+                "only_need_context": True,
+                "top_k": top_k,
+            },
+        )
+        r.raise_for_status()
+        return r.json()
+
+
+if __name__ == "__main__":
+    mcp.run()