mcp

The mcp-server provided by APIVerve gives you access to a large collection of APIs through the Model Context Protocol (MCP). Once running, the server exposes a uniform MCP interface that lets you connect to and orchestrate requests against 249+ APIs without writing custom adapters for each one. You can configure authentication keys, select which APIs to expose, and then issue model-context requests that the server translates into concrete API calls and returns structured responses. The interface is designed to be developer-friendly, enabling quick experimentation, request chaining, and simple integration into your own applications via MCP-compatible clients.

Prerequisites:

• Python 3.8+ installed on your system
• Basic shell access (bash/zsh on macOS/Linux, PowerShell or Command Prompt on Windows)
• Optional: Python virtual environment support

Step 1: Download and extract

• Download the mcp-server release zip and extract it to a working directory.

Step 2: Create and activate a virtual environment (recommended)

• macOS/Linux: python -m venv venv source venv/bin/activate
• Windows: python -m venv venv .\venv\Scripts\activate

Step 3: Install dependencies

• Ensure you are in the project root (where requirements.txt may reside).
• Install dependencies (if a requirements file is provided): pip install -r requirements.txt

Step 4: Run the MCP server

• Start the server with: python -m apiverve_mcp

Step 5: Verify operation

• Monitor the console output for startup messages indicating the MCP server is listening on its configured port.
• If you have a config file, ensure it points to the APIs you want to expose and that API keys are correctly set.

Note: If the project provides a specific installation script or additional setup steps in its documentation, follow those steps exactly. The commands above assume a standard Python package layout for an MCP server.

Environment variables and configuration tips:

• If the server supports environment-based configuration, set API keys and endpoint permissions via environment variables (e.g., API_KEY, API_SECRET, MCP_PORT).
• If you use a config file, ensure it lists the APIs you want to enable and any required authentication details.
• Common issues include missing dependencies, incorrect Python version, or firewall/network restrictions blocking API access.
• Check logs for error messages related to authentication, network access, or missing API permissions and adjust your environment accordingly.