MCP Servers - OpenHarness

Agents can connect to Model Context Protocol servers. Tools from MCP servers are merged into the agent’s toolset alongside any static tools.

Configuration

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.