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Velo Payments MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-velo-payments-apis": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "JSON string with configuration",
        "SECURITY": "Security-related environment variables",
        "CONFIG_PATH": "Path to config JSON file (e.g., mcp_server/mcp_config.json)"
      }
    }
  }
}

An MCP (Model Context Protocol) Server exposes a programmable interface for a specific API by translating client requests into actions against a defined data model. It lets you plug an OpenAPI-driven API into an MCP workflow, enabling consistent communication with MCP clients in your environment and facilitating testing, integration, and automation.

How to use

You run the MCP server as a local process and connect your MCP client to it. The server supports multiple transport modes, including stdio for local process communication, as well as streaming HTTP variants. Start the server, then configure your client to communicate via the chosen transport. You can control how the server loads its configuration through environment variables or a configuration file.

How to install

Prerequisites: Python 3.9 or newer, and the Python package manager tools pip and uv.

1. Clone the project repository.

2. Change into the project directory.

3. Install development dependencies.

Option A: Use the development install script if you are using the dev container.

pip install -e ".[dev]"

Option B: Install directly with pip without the dev container.

pip install -e ".[dev]"

Option C: Use the uv tool to install in editable mode.

uv pip install --editable ".[dev]"

4. Run the MCP server in stdio mode.

python mcp_server/main.py stdio

Additional notes

Configuration can be provided via environment variables. The following are commonly used: CONFIG_PATH (path to a JSON configuration file), CONFIG (a JSON string containing the configuration), and SECURITY (environment variables related to security parameters such as API keys). The startup behavior reads from the __main__ block in the main script to determine how these are loaded.

Development and quality tooling include linting, static type checking, and tests. Lint with ruff, format with ruff, run static analysis with the provided script, and execute tests with coverage. Pre-commit hooks are enabled to run on each commit.