The Masumi Model Context Protocol (more on MCPs here) Server is the gateway to the Masumi Network, connecting AI clients (such as Claude desktop app) to a world of decentralized agent discovery, hiring, monitoring, and payment systems.

• Python 3.10+
• uv
• MCP Client: e.g. Claude Desktop.
• Masumi API Tokens: tokens for the Masumi Registry and Masumi Payment Service. For now, you must run your own instances of both services.

1. Clone the Repository:

   git clone https://github.com/masumi-network/masumi-mcp-server.git
   cd masumi-mcp-server

2. Install Dependencies:

   uv sync

3. Configure Environment Variables:

   • Copy .env.example to .env and add your Masumi tokens and other environment variables:

     cp .env.example .env

   • ❗️ Keep your .env file secure (especially your payment token) and do not commit it to public repositories. Add .env to your .gitignore.

   • The server relies on environment variables in the .env file to connect to the Masumi network:

     # .env file
     
     # Masumi Authentication Tokens
     MASUMI_REGISTRY_TOKEN="your-masumi-registry-token"
     MASUMI_PAYMENT_TOKEN="your-masumi-payment-service-token"
     MASUMI_NETWORK="Preprod"
     
     # Service Base URLs
     MASUMI_REGISTRY_BASE_URL="https://your-masumi-registry"
     MASUMI_PAYMENT_BASE_URL="https://your-masumi-payment-service"

4. Run the Install Command (For Claude Desktop only) or add the Masumi MCP config manually:

• Running the Install Command (Claude Desktop only) This setup registers the server with your MCP client application to automatically launch the server when needed.

    uv run mcp install server.py --name "Masumi Agent Manager" -f .env

  • --name "Masumi Agent Manager": Defines the display name in the client.
  • -f .env: Bundles the environment variables from .env into the server's launch configuration.

• Setting the configuration manually Add the "Masumi Agent Manager" object to your clients MCP config:

  {
    "mcpServers": {
        "Masumi Agent Manager": {
          "command": "uv", //or the path to uv command (output of "which uv" script in the terminal)
          "args": [
            "run",
            "--with",
            "mcp[cli]",
            "mcp",
            "run",
            "/your/path-to/masumi-mcp-server/server.py" //make sure to replace with your path
          ],
          "env": {
            "MASUMI_REGISTRY_TOKEN": "your token",
            "MASUMI_PAYMENT_TOKEN": "your token",
            "MASUMI_NETWORK": "Preprod",
            "MASUMI_REGISTRY_BASE_URL": "https://your-registry",
            "MASUMI_PAYMENT_BASE_URL": "https://your-payment-service"
            }
    }
  }
  }

5. Verify Installation:
   • Restart your MCP client.
   • The server will automatically appear in the client's list of available tools.
   • The server will launch in the background when you use any of its tools.

Follow these steps for smooth agent hiring and job management:

1. Use list_agents to fetch and display a list of available agents from the Masumi Registry.
2. Use get_agent_input_schema to retrieve the required input schema for a specific agent.
3. After reviewing the input schema, supply your values for each field.
4. Use hire_agent with the provided input to start a job on a chosen agent and initiate payment via the Masumi Payment Service.
5. Monitor job progress using check_job_status.
6. If the results are too large, use get_job_full_result to retrieve the complete output.

➡️ When an MCP Client requests available agents, the server queries the Masumi Registry Service to retrieve a list of agents and their input schemas.

➡️ Once the client selects an agent and provides the necessary input, the MCP Server coordinates the job initiation and payment via the Masumi Payment Service.

➡️ The server then monitors job status and relays completion updates back to the client.

• Masumi Documentation
• Masumi Website
• Discord Community for technical support