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# How to Configure MCP Tools in nanobot
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This guide adds an MCP server to nanobot so the agent can use external tools
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through the Model Context Protocol.
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## What you will build
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- a working nanobot agent
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- one MCP server entry in `~/.nanobot/config.json`
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- a restricted set of MCP tools exposed to the model
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## When to use this
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Use MCP when the capability you need already exists as an MCP server, or when
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you want external tools to be managed outside nanobot core.
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## Install
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```bash
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python -m pip install nanobot-ai
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nanobot onboard --wizard
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nanobot agent -m "Hello!"
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```
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Install the MCP server runtime separately. Many examples use `npx`, `uvx`, or a
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remote HTTP endpoint.
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## Minimal working example
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Add this to `~/.nanobot/config.json`:
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```json
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{
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"tools": {
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"mcpServers": {
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"filesystem": {
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"command": "npx",
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"args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"],
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"enabledTools": ["read_file"]
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}
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}
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}
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}
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```
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Restart nanobot and ask a question that requires the MCP tool.
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## Production notes
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- Prefer `enabledTools` over exposing every tool by default.
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- Use `toolTimeout` for slow MCP operations.
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- Use HTTP MCP only for endpoints you trust.
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- Keep MCP server commands stable and versioned in deployment docs or scripts.
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## Security notes
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- Stdio MCP starts a local process; review the command before enabling it.
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- HTTP/SSE MCP uses nanobot's SSRF guard.
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- Allow private HTTP MCP hosts only with narrow `tools.ssrfWhitelist` CIDRs.
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- Do not place secrets in command arguments when environment variables or
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headers can be used.
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## Troubleshooting
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- Run the MCP command outside nanobot first.
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- Start `nanobot gateway --verbose` and inspect tool registration logs.
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- If an HTTP MCP URL is blocked, check whether it points to loopback or a
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private address that needs explicit allowlisting.
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## Related nanobot docs
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- [MCP tools for AI agents](./mcp-tools-for-ai-agents.md)
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- [Configuration: MCP](../configuration.md#mcp-model-context-protocol)
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- [Security](../configuration.md#security)
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