Universal MCP

Universal MCP acts as a middleware layer for your API applications, enabling seamless integration with various services through the Model Control Protocol (MCP). It simplifies credential management, authorization, dynamic app enablement, and provides a robust framework for building and managing AI-powered tools.

🌟 Features

• MCP (Model Control Protocol) Integration: Seamlessly works with MCP server architecture for standardized agent-tool communication.
• Simplified API Integration: Connect to services like GitHub, Google Calendar, Gmail, Reddit, Tavily, and more with minimal code. See AgentR for a list of available applications.
• Managed Authentication: Built-in support for API keys and OAuth-based authentication flows, often managed via the AgentR platform.
• Extensible Architecture: Easily build and add new app integrations with minimal boilerplate using provided base classes and generation tools.
• Credential Management: Flexible and secure storage options for API credentials (memory, environment variables, system keyring).
• Comprehensive Tool Management: Robust tool registration, Pydantic-based validation, automatic docstring parsing, and execution capabilities. Supports conversion between MCP, LangChain, and OpenAI tool formats.
• Multiple Server Types: Configurations for local development, AgentR-connected dynamic app loading, and single-application servers.
• Playground Environment: Includes an interactive Streamlit-based playground for testing agents and tools.

🔧 Installation

Install Universal MCP using pip:

pip install universal-mcp

🚀 Quick Start

Important Prerequisite: AgentR API Key (If Using AgentR Integration)

If you plan to use integrations with type: "agentr" (for services like GitHub, Gmail, Notion via the AgentR platform), or if you run the MCP server itself with type: "agentr", you first need an AgentR API key:

1. Visit https://agentr.dev to create an account and generate an API key from your dashboard.
2. Set it as an environment variable before running the MCP server:

   export AGENTR_API_KEY="your_api_key_here"
   

1. Create a Configuration File (e.g., config.json)

This file defines the server settings, credential stores, and the applications to load with their respective integrations.

{
  "name": "My Local MCP Server",
  "description": "A server for testing applications locally",
  "type": "local", // "local" or "agentr"
  "transport": "sse", // "sse", "stdio", or "http"
  "port": 8005, // Relevant for "sse" or "http"
  "store": {
    // Default store for integrations
    "name": "my_mcp_store",
    "type": "keyring" // "keyring", "environment", or "memory"
  },
  "apps": [
    {
      "name": "zenquotes", // App slug (e.g., from agentr.dev)
      "integration": null // No authentication needed for this app
    },
    {
      "name": "tavily",
      "integration": {
        "name": "TAVILY_API_KEY", // Unique name for this credential if type is "api_key"
        "type": "api_key",
        "store": {
          // Override default store for this specific app
          "type": "environment" // Looks for TAVILY_API_KEY env var
        }
      }
    },
    {
      "name": "github",
      "integration": {
        "name": "github", // Matches the service name in AgentR
        "type": "agentr" // Uses AgentR platform for auth/creds
      }
    }
  ]
}

Notes on config.json:

• type: "local": Runs applications defined directly in the config's apps list.
• type: "agentr": Connects to the AgentR platform to dynamically load user-enabled apps (ignores the apps list in the config) and handle credentials. Requires AGENTR_API_KEY environment variable.
• store: Defines credential storage.
  • environment: Looks for an environment variable named <INTEGRATION_NAME_UPPERCASE> (e.g., TAVILY_API_KEY for the example above).
  • keyring: Uses the system's secure credential storage.
  • memory: Transient storage, lost when the server stops.
• integration: Configures authentication for each app.
  • type: "agentr": Uses the AgentR platform for OAuth/credential management.
  • type: "api_key": Uses the specified store to retrieve the key.

2. Run the Server via CLI

Ensure any required environment variables (like TAVILY_API_KEY for the Tavily example, or AGENTR_API_KEY if using "agentr" type server/integrations) are set.

universal_mcp run -c config.json

The server will start, load the configured applications (or connect to AgentR if type: "agentr"), and listen for connections based on the transport type.

🛠️ Using the Playground

The playground directory provides a runnable Streamlit application for interacting with agents that can use tools from an MCP server.

Prerequisites:

• local_config.json: This file must exist in the project root directory (the same directory as this README.md). It configures the local MCP server that the playground's agent can connect to if you choose to run one. For an example, see the local_config.json structure in the Playground README.
• Dependencies: Install playground-specific dependencies. If you have the project cloned, you might install them via:

  pip install -e .[playground]
  # or manually install fastapi, streamlit, uvicorn, langchain-openai, etc.
  

Running the Playground:

The easiest way is to use the automated startup script from the project root directory:

python playground

This script will:

1. Optionally start a local MCP server (based on your local_config.json) if you confirm.
2. Launch the Streamlit application.

For more detailed setup, manual startup instructions, and an explanation of the local_config.json for the playground, please refer to the Playground README.

🧩 Available Applications

Universal MCP can integrate with a wide variety of applications. For a list of publicly available applications and their slugs (e.g., "github", "google-calendar"), please visit AgentR Applications. Applications are typically installed dynamically by Universal MCP from their respective repositories when first referenced by slug.

Authentication Type Notes:

• OAuth (via AgentR): Usually requires configuring the app's integration with type: "agentr" in your ServerConfig. This leverages the AgentR platform for the OAuth flow and requires the AGENTR_API_KEY to be set.
• API Key (via Integration): Requires configuring type: "api_key" for the app's integration in your ServerConfig, along with a store (like environment or keyring) to specify where the API key is located.

🔐 Integration Types

Universal MCP supports different ways to handle authentication for applications:

1. API Key Integration (type: "api_key")

For services that authenticate via simple API keys.

// In your ServerConfig apps array:
{
  "name": "tavily",
  "integration": {
    "name": "TAVILY_API_KEY", // Used by the store (e.g., as env var name)
    "type": "api_key",
    "store": {
      "type": "environment" // Or "keyring", "memory"
    }
  }
}

2. AgentR Integration (type: "agentr")

Recommended for services integrated with the AgentR platform, which typically handles OAuth flows or centrally managed credentials. Requires the AGENTR_API_KEY environment variable to be set for the MCP server process.

// In your ServerConfig apps array:
{
  "name": "github",
  "integration": {
    "name": "github", // Matches the service name configured in AgentR
    "type": "agentr"
  }
}

When an action requiring authorization is called, the AgentRIntegration will prompt the user (via the MCP client) to visit a URL to complete the OAuth flow managed by AgentR. This is also the default integration type for apps if the main server config is type: "agentr".

3. Direct OAuth Integration (type: "oauth")

While AgentRIntegration is generally preferred for OAuth, a direct OAuthIntegration class exists. However, it requires manual configuration of client IDs, secrets, and callback handling, which is more complex to set up outside the AgentR platform.

🤖 CLI Usage

Universal MCP includes a powerful command-line interface:

# Run the MCP server using a configuration file
universal_mcp run -c config.json

# Initialize a new MCP application project structure
universal_mcp init --app-name my-cool-app --o ./my-apps --integration-type api_key

# Generate API client code and application structure from an OpenAPI schema
universal_mcp generate -s <path_to_schema.json_or_yaml> -o <path/to/app_output_directory> --c CustomAppClassName
# Example: universal_mcp generate -s notion_api.yaml -o ./custom_apps/notion --c MyNotionApp

# Preprocess an OpenAPI schema using an LLM to fill/enhance descriptions
universal_mcp preprocess -s <path_to_input_schema.json_or_yaml> -o <path_to_processed_schema.json_or_yaml>

# Generate Google-style docstrings for functions in a Python file using an LLM
universal_mcp docgen <path/to/app_file.py>

# Generate a README.md for a generated application file
universal_mcp readme <path/to/app_file.py>

# Install MCP configuration for supported desktop apps (e.g., Claude, Cursor)
# Requires an AgentR API key for configuration.
universal_mcp install claude
universal_mcp install cursor

# Check installed version (standard typer command)
universal_mcp --version

📋 Requirements

• Python 3.10+
• Key Dependencies (installed automatically via pip, see pyproject.toml for full list):
  • mcp-server
  • loguru
  • typer
  • httpx
  • pydantic
  • pyyaml
  • keyring (for KeyringStore)
  • litellm (for docgen and preprocess commands)
  • uv (used internally for dynamic package installation)

📚 Documentation

For more detailed information about specific components:

• Applications Framework
• Tool Management
• Server Implementations
• Credential Stores
• Integration & Authentication
• Playground Usage

📝 License

This project is licensed under the MIT License. See the LICENSE file for details.