> ## Documentation Index
> Fetch the complete documentation index at: https://docs.open-harness.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# MCP Servers

> Connect to Model Context Protocol servers for external tools

Agents can connect to [Model Context Protocol](https://modelcontextprotocol.io) servers. Tools from MCP servers are merged into the agent's toolset alongside any static tools.

## Configuration

```typescript theme={"dark"}
const agent = new Agent({
  name: "dev",
  model: openai("gpt-5.4"),
  tools: { ...fsTools, bash },
  mcpServers: {
    github: {
      type: "stdio",
      command: "npx",
      args: ["-y", "@modelcontextprotocol/server-github"],
      env: { GITHUB_TOKEN: process.env.GITHUB_TOKEN },
    },
    weather: {
      type: "http",
      url: "https://weather-mcp.example.com/mcp",
      headers: { Authorization: "Bearer ..." },
    },
  },
});

// MCP connections are established lazily on first run()
for await (const event of agent.run([], "What PRs are open?")) {
  // ...
}

// Clean up MCP connections when done
await agent.close();
```

## Transport Types

Three transport types are supported:

| Transport | Use case                                                               |
| --------- | ---------------------------------------------------------------------- |
| `stdio`   | Local servers — spawns a child process, communicates over stdin/stdout |
| `http`    | Remote servers via Streamable HTTP (recommended for production)        |
| `sse`     | Remote servers via Server-Sent Events (legacy)                         |

## Tool Namespacing

When multiple MCP servers are configured, tools are namespaced as `serverName_toolName` to avoid collisions. With a single server, tool names are used as-is.

## Lazy Connection

MCP connections are established lazily on the first `run()` call and cached for the agent's lifetime. This follows the same pattern as skills discovery. Always call `agent.close()` when done to clean up connections.