---
title: MCP Documentation Search | LlamaIndex OSS Documentation
description: Connect to our hosted MCP server to search LlamaIndex documentation
---

As part of the LlamaIndex documentation, we serve a hosted MCP server that allows any agent to search the LlamaIndex documentation.

The hosted MCP server is available at the following URL:

```
https://developers.llamaindex.ai/mcp
```

The server ships with the following tools:

1. `search_docs` — a basic lexical search using BM25
2. `grep_docs` — exact search using regex
3. `read_doc` — provides an interface to read the entire contents of any given page path

![MCP Server](/_astro/mcp.Bn5KN2fe_2f2ziQ.png)

## Configure your Agent

### Cursor

You can [click to install to cursor directly](cursor://anysphere.cursor-deeplink/mcp/install?name=llama-index-docs\&config=eyJ1cmwiOiJodHRwczovL2RldmVsb3BlcnMubGxhbWFpbmRleC5haS9tY3AifQ%3D%3D) or add the following to your `mcp.json` configuration:

```
{
  "mcpServers": {
    "llama_index_docs": {
      "url": "https://developers.llamaindex.ai/mcp"
    }
  }
}
```

### Claude Code

Add the documentation search tools to your Claude Code agent with a single command:

Terminal window

```
claude mcp add llama-index-docs --transport http https://developers.llamaindex.ai/mcp
```

### OpenAI Codex

Add the documentation search tools to your OpenAI Codex agent by adding the following section to your `config.toml`:

Terminal window

```
[mcp_servers.llama_index_docs]
url = "https://developers.llamaindex.ai/mcp"
```

### LlamaIndex Agents

Install llama-index and the MCP tools package:

Terminal window

```
pip install llama-index llama-index-tools-mcp
```

And then directly use the MCP tools in your agent:

```
from llama_index.core.agent import FunctionAgent, ToolCall, ToolCallResult
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import McpToolSpec, BasicMCPClient




async def main():
    client = BasicMCPClient("https://developers.llamaindex.ai/mcp")
    tool_spec = McpToolSpec(client=client)
    tools = await tool_spec.to_tool_list_async()


    agent = FunctionAgent(
        llm=OpenAI(model="gpt-4.1", api_key="sk-..."),
        tools=tools,
        system_prompt="You are a helpful assistant that has access to tools to search the LlamaIndex documentation."
    )


    while True:
        query = input("Query: ")
        handler = agent.run(query)
        async for ev in handler.stream_events():
            if isinstance(ev, ToolCall):
                print(f"Calling tool {ev.tool_name} with input {ev.tool_kwargs}")
            if isinstance(ev, ToolCallResult):
                print(f"Tool {ev.tool_name} returned {ev.tool_output}")


        resp = await handler
        print("")
        print(resp)
        print("=================")


if __name__ == "__main__":
    import asyncio
    asyncio.run(main())
```