# MCP Integration

OM1 agents can now connect to external tools like Slack, Notion, weather APIs, and more — all through the Model Context Protocol (MCP). No custom integrations required.

### What is MCP?

MCP is an open standard that lets AI agents discover and use tools dynamically. Think of it as **USB for AI** — plug in a server, and your agent instantly knows what tools are available.

### Architecture

![](/files/Rk83DvEROrAnuvS9fzcY)

#### Key Components

| Component            | Description                                                                                    |
| -------------------- | ---------------------------------------------------------------------------------------------- |
| **OM1 Agent**        | The main agent runtime for the machine                                                         |
| **Modes**            | Each mode can have its own MCP servers, system prompt, inputs, and actions                     |
| **MCP Servers**      | Per-mode configuration that defines which external tools are available in that particular mode |
| **Orchestrator**     | Coordinates communication between the agent and external services                              |
| **MCPClientManager** | Manages connections to MCP servers, discovers tools, and routes tool calls                     |
| **MCP Tools**        | External services like Slack, Google Maps, Weather APIs, Notion, and more                      |
| **Robot Interface**  | Physical or simulated robot that interacts with the real world                                 |

#### Per-Mode MCP Servers

Each mode operates independently with its own set of MCP servers. For example:

```
Mode 1 ──► [Slack, Google Maps]     ──► MCPClientManager instance 1
Mode 2 ──► [Weather, News]          ──► MCPClientManager instance 2
Mode 3 ──► (no MCP servers)         ──► Offline mode
```

This enables:

* **Isolation**: Different modes access different tools
* **Flexibility**: Hot-swap capabilities without code changes

#### Install Node

MCP servers typically run via `npx`, which requires Node.js to be installed.

Check if you already have it installed by running the following commands -

```bash
node --version
npm --version
```

If you don't have node installed on your system, follow the steps [here](https://nodejs.org/en/download/current).

#### Add MCP Servers to Your Config

| Field       | Type     | Required                  | Description                                                                           | Example                                              |
| ----------- | -------- | ------------------------- | ------------------------------------------------------------------------------------- | ---------------------------------------------------- |
| `name`      | *string* | Required                  | Server identifier                                                                     | `"google-maps"`                                      |
| `transport` | *string* | Required                  | How to connect: `stdio` (subprocess), `sse` (streaming), or `http` (request/response) | `"stdio"`                                            |
| `command`   | *string* | Required                  | Executable to launch                                                                  | `"npx"`                                              |
| `args`      | *array*  | Optional                  | Arguments for the command                                                             | `["-y", "@modelcontextprotocol/server-google-maps"]` |
| `env`       | *object* | Optional                  | Environment variables required by the server (e.g., API keys, tokens)                 | `{"API_KEY": "your-api-key"}`                        |
| `url`       | *string* | Required for `sse`/`http` | Server endpoint URL                                                                   | `"http://localhost:3000/sse"`                        |
| `headers`   | *object* | Optional                  | HTTP headers for `sse`/`http` transport                                               | `{"Authorization": "Bearer token"}`                  |

### How It Works

```
┌─────────────────────────────────────────────────────────────┐
│                        OM1 Agent                            │
│                                                             │
│   Config ──► load_mcp() ──► MCPClientManager                │
│                                   │                         │
│                                   ├── Discovers tools       │
│                                   ├── Manages connections   │
│                                   └── Executes tool calls   │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
                ┌─────────────────────────┐
                │     MCP Servers         │
                │  (Slack, Maps, etc.)    │
                └─────────────────────────┘
```

1. **Configuration**: MCP servers are defined in your mode's config file
2. **Initialization**: `MCPClientManager` launches and connects to each server
3. **Discovery**: Tools are automatically discovered from connected servers
4. **Execution**: When the LLM decides to use a tool, `MCPClientManager` routes the call

Example config file [conversation\_mcp](https://github.com/OpenMind/OM1/blob/main/config/conversation_mcp.json5)

### Available MCP Servers

Browse community-maintained MCP servers:

* [Official MCP Servers](https://github.com/modelcontextprotocol/servers)
* Slack, GitHub, Google Maps, Filesystem, and many more

### Next Steps

* [Configuration Guide](https://github.com/OpenMind/OM1/blob/main/docs/core-concepts/3_configuration.md) — Learn more about OM1 config files
* [MCP Specification](https://modelcontextprotocol.io) — Official MCP documentation


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# Agent Instructions: Querying This Documentation

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Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.openmind.com/mcp/mcp-integration.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.