How to Add MCP Tools to an AI Agent with nanobot

nanobot can connect MCP servers and expose their tools to the agent alongside built-in file, shell, web, cron, image generation, and subagent tools.

What you will build

a working nanobot agent
one MCP server configured in config.json
a restricted set of tools available to the model

When to use this

Use MCP when a tool already exists as an MCP server, when another application publishes an MCP adapter, or when you want a clean boundary between nanobot and external tool logic.

Install

python -m pip install nanobot-ai
nanobot onboard --wizard
nanobot agent -m "Hello!"

Install the MCP server's own runtime separately. For example, many local MCP servers use npx or uvx.

Minimal working example

Add a stdio MCP server to ~/.nanobot/config.json:

{
  "tools": {
    "mcpServers": {
      "filesystem": {
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"],
        "enabledTools": ["read_file"]
      }
    }
  }
}

Restart nanobot, then ask a question that needs the MCP tool.

Production notes

Use enabledTools to expose only the tools the agent actually needs.
Set toolTimeout for slow MCP servers.
Prefer stdio MCP for local tools and HTTP MCP for trusted remote services.
Keep MCP server install/update steps outside nanobot config when possible.

Security notes

HTTP/SSE MCP URLs use the same SSRF guard as web fetch.
Local/private HTTP endpoints require an explicit tools.ssrfWhitelist entry.
Stdio MCP servers run local processes; review their command and arguments.
Do not pass secrets in command-line args when environment variables or headers are available.

Troubleshooting

Start nanobot gateway --verbose and check MCP startup logs.
Confirm the MCP command works by itself before debugging nanobot.
If an HTTP MCP server is blocked, review the SSRF whitelist and use a narrow host CIDR.

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