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Multi-server MCP AI Agent

Multi-server MCP AI Agent

Local
github.com/IsaacDsouzaAI & Agents0Updated 73w ago
Repository

About Multi-server MCP AI Agent

Multi-server MCP AI Agent is a Python application for automating meeting, email, and document tasks through prompts. Its setup includes Gmail authentication and a token-generation step before running the application.

Key features

  1. 01Automate meetings, emails, and documents via prompts
  2. 02Authenticate with Google OAuth credentials
  3. 03Generate a token with tokengen.py
  4. 04Run the application with app.py

Use cases

  1. 01Automate email-related tasks
  2. 02Handle meeting tasks through prompts
  3. 03Automate document tasks

MCP support

The project is described as an MCP AI agent, but the README does not specify how it connects to or manages MCP servers.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Multi-server MCP AI Agent

Automates your meetings, emails & docs via prompts

Setup Steps

  1. Clone and enter the project

git clone https://github.com/IsaacDsouza/mcp-with-multiple-servers
cd mcp-with-multiple-servers

  1. Create virtual environment and activate it

  uv venv
  .venv\Scripts\activate

  1. Install dependencies:

uv add -r requirements.txt

  1. Create a Google Cloud Project and obtain credentials:

    a. Create a Google Cloud Project:

    • Go to Google Cloud Console
    • Create a new project or select an existing one
    • Enable the Gmail API for your project

    b. Create OAuth 2.0 Credentials:

    • Go to "APIs & Services" > "Credentials"
    • Click "Create Credentials" > "OAuth client ID"
    • Choose either "Desktop app" or "Web application" as application type
    • Give it a name and click "Create"
    • For Web application, add http://localhost:3000/oauth2callback to the authorized redirect URIs
    • Download the JSON file of your client's OAuth keys
    • Rename the key file to gcp-oauth.keys.json

  2. Run Authentication:

    You can authenticate in two ways:

    a. Global Authentication (Recommended):

    # First time: Place gcp-oauth.keys.json in your home directory's .gmail-mcp folder
mkdir -p ~/.gmail-mcp
mv gcp-oauth.keys.json ~/.gmail-mcp/

# Run authentication from anywhere
npx @gongrzhe/server-gmail-autoauth-mcp auth

    b. Local Authentication:

    # Place gcp-oauth.keys.json in your current directory
# The file will be automatically copied to global config
npx @gongrzhe/server-gmail-autoauth-mcp auth

    The authentication process will:

    • Look for gcp-oauth.keys.json in the current directory or ~/.gmail-mcp/
    • If found in current directory, copy it to ~/.gmail-mcp/
    • Open your default browser for Google authentication
    • Save credentials as ~/.gmail-mcp/credentials.json

    Note:

    • After successful authentication, credentials are stored globally in ~/.gmail-mcp/ and can be used from any directory
    • Both Desktop app and Web application credentials are supported
    • For Web application credentials, make sure to add http://localhost:3000/oauth2callback to your authorized redirect URIs

  3. Run Token generator:

uv run tokengen.py

  1. Run Application

uv run app.py

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.