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Subscriptions API V3 MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-subscriptions-api-v3": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "{...} (JSON string with your MCP config)",
        "SECURITY": "API keys or other security parameters",
        "CONFIG_PATH": "mcp_server/mcp_config.json"
      }
    }
  }
}

You run an MCP server that connects to a predefined API and exposes a stable, protocol-driven interface for clients to interact with the Subscriptions API v3. This server helps you manage context-aware requests and keeps interactions decoupled from specific client implementations, making integration straightforward across languages and platforms.

How to use

Start the server in stdio mode to run locally and interact with your MCP client. The server reads its configuration from environment variables or a JSON configuration file. To begin, launch the server and point your MCP client at the local process.

How to install

Prerequisites: Install Python 3.9 or newer. Ensure you have pip and a runner available as needed.

# Prerequisites
python3 --version
# Should be Python 3.9+
pip --version

# Optional: install uv for local testing
pip install --editable .

Additional sections

Configuration and security are handled through environment variables or a JSON config file. The built-in options let you specify where to load configuration from, as well as security parameters to control access.

Run command for the MCP server in stdio mode: ``text``

Configuration notes

The server supports loading configuration from a file or inline JSON. Use CONFIG_PATH to point at a file path or CONFIG to provide a JSON string. You can also supply SECURITY-specific variables to control access to the MCP endpoints.

Troubleshooting and tips

If the server fails to start, verify Python 3.9+ is installed, the required dependencies are installed, and that the environment variables CONFIG_PATH or CONFIG are correctly set. Check for clear error messages indicating missing files or invalid JSON.

Available tools

linting

Ruff is used for linting and formatting to enforce consistent code quality.

static analysis

Static analysis tools (mypy, bandit, semgrep) are run to catch type issues and potential security risks.

testing

Pytest is used to run tests and generate coverage reports.

pre-commit

Pre-commit hooks help ensure code quality before each commit.