agentic-compute-mcp-codelad1304 1.0.7

A secure, monetized Python sandbox for data optimization and Matplotlib rendering via x402.

agentic-compute-mcp

Agentic API Platform: MCP Bridge

mcp-name: io.github.codelad1304/agentic-compute

A high-performance Model Context Protocol (MCP) server providing premium computational services to autonomous AI agents. This bridge connects Claude and other MCP-compatible LLMs to secure, cloud-hosted endpoints for advanced mathematical optimization and data visualization.

Built with FastMCP and FastAPI, this system leverages the x402 protocol for automated Machine-to-Machine (M2M) microtransactions on the Base network (USDC settlement).

Features

Native MCP Integration: Instantly expose computational tools to Claude Desktop and other MCP clients.

M2M Monetization (x402): Seamless crypto-based settlement per API call. Agents automatically pay for compute using USDC on Base.

Bypass LLM UI Limits: Overcomes LLM token limits by processing massive data structures (like Base64 image matrices) efficiently in the backend.

Available Tools (Endpoints)

This MCP server currently exposes the following premium tools to AI agents:

1. execute_code (Cost: 0.10 USDC)

• Executes arbitrary, agent-generated Python code in a highly secure, isolated remote Azure sandbox.

• Capabilities: Protects the host machine from untrusted code execution while returning standard output (stdout) and standard error (stderr) directly to the agent.

2. sanitize_csv (Cost: 0.25 USDC)

• Cleans and normalizes raw, unstructured CSV data into strict JSON arrays.

• Capabilities: Automatically normalizes headers, handles null values, and drops empty rows, preparing messy data for immediate mathematical modeling.

3. optimize_ga (Cost: 0.50 USDC)

• Runs a high-performance Genetic Algorithm (GA) to optimize data models (Polynomial, Logistic, Exponential).

• Capabilities: Smart parameter initialization, proportional mutation to prevent premature convergence, and high-accuracy curve fitting (achieves <1% MAPE).

• Ideal for: Load forecasting, predictive modeling, and complex hyperparameter tuning.

4. generate_plot (Cost: 0.30 USDC)

• A Matplotlib-based rendering engine that generates production-ready charts and graphs.

• Capabilities: Bypasses LLM token generation limits by natively drawing data and returning lightweight base64 image streams directly to the host machine.

• Ideal for: Visualizing optimization results, time-series data, and mathematical models.

Installation & Setup

1. Install via PyPI:

pip install agentic-compute-mcp-codelad1304

2. Configure Environment Variables: Create a .env file or export the following variable in your terminal to allow your local MCP client to process agentic payments:

export EVM_PRIVATE_KEY=your_private_key_here

Using with Claude Desktop

• To install this server for Claude Desktop, add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "agentic-compute": {
      "command": "agentic-compute-mcp",
      "args": [],
      "env": {
        "EVM_PRIVATE_KEY": "your_private_key_here"
      }
    }
  }
}

License

This project is licensed under the MIT License - see the LICENSE file for details. mcp-name: io.github.codelad1304/agentic-compute