Multi-server MCP AI Agent

@IsaacDsouza

About Multi-server MCP AI Agent

Agentic AI platform that automates personal tasks by integrating with services such as Gmail, Notion, Slack, Zoom, and Google Drive via a modular tool marketplace. MCP, LangChain, MongoDB, Python

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-with-multiple-servers": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Tools

No tools detected

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Overview

What is Multi-server MCP AI Agent?

An MCP server that automates meetings, emails, and documents via natural language prompts. It integrates with the Google Gmail API and supports multiple MCP servers to orchestrate automation tasks.

How to use Multi-server MCP AI Agent?

Clone the repository, set up a Python virtual environment with uv, install dependencies, create a Google Cloud project and enable the Gmail API, generate OAuth 2.0 credentials, run the authentication process via npx, execute the token generator script, and finally run the application with uv run app.py.

Key features of Multi-server MCP AI Agent

Automates meetings, emails, and docs via prompts
Integrates multiple MCP servers for orchestration
Uses Google OAuth 2.0 for secure Gmail access
Local installation with Python virtual environment
Global credential storage in ~/.gmail-mcp/

Use cases of Multi-server MCP AI Agent

Automating email replies and summarization
Scheduling and managing meetings from prompts
Generating or updating documents via natural language
Chaining multiple MCP servers for complex workflows
Streamlining daily office tasks with AI agents

FAQ from Multi-server MCP AI Agent

What are the prerequisites for running this server?

You need Python (with uv installed), Node.js (for npx), and a Google Cloud project with the Gmail API enabled.

How do I obtain and set up OAuth credentials?

Create a Google Cloud project, enable the Gmail API, and generate an OAuth 2.0 client ID (desktop or web app). Download the JSON key file and rename it to gcp-oauth.keys.json.

Where are authentication credentials stored?

After authentication, credentials are saved globally in ~/.gmail-mcp/credentials.json. The OAuth key file can be placed in the current directory or ~/.gmail-mcp/.

What authentication methods are supported?

Both Desktop app and Web application OAuth credentials are supported. For web apps, add http://localhost:3000/oauth2callback to the authorized redirect URIs.

What is the token generator for?

The tokengen.py script (run with uv run tokengen.py) processes the OAuth credentials and generates tokens needed for the main application.

Frequently asked questions

What are the prerequisites for running this server?

You need Python (with uv installed), Node.js (for npx), and a Google Cloud project with the Gmail API enabled.

How do I obtain and set up OAuth credentials?

Create a Google Cloud project, enable the Gmail API, and generate an OAuth 2.0 client ID (desktop or web app). Download the JSON key file and rename it to `gcp-oauth.keys.json`.

Where are authentication credentials stored?

After authentication, credentials are saved globally in `~/.gmail-mcp/credentials.json`. The OAuth key file can be placed in the current directory or `~/.gmail-mcp/`.

What authentication methods are supported?

Both Desktop app and Web application OAuth credentials are supported. For web apps, add `http://localhost:3000/oauth2callback` to the authorized redirect URIs.

What is the token generator for?

The `tokengen.py` script (run with `uv run tokengen.py`) processes the OAuth credentials and generates tokens needed for the main application.

Comments

Basic information

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