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io.github.Mangomunchr/farpy

Official registry Other

FARPY routes GPU workloads to qualified compute and returns verified artifacts and receipts.

Source code Documentation

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http farpy 'https://api.farpy.com/mcp'
JSON configuration (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "farpy": {
            "type": "http",
            "url": "https://api.farpy.com/mcp"
        }
    }
}

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  1. FARPY
  2. Public workload
  3. Agent / API access
  4. Agent discovery
  5. Public surfaces
  6. Local MCP / Glama
  7. Scope

FARPY

Verified GPU compute for humans, applications, and agents.

FARPY accepts bounded GPU workloads, executes them asynchronously, delivers completed artifacts, and issues verifiable execution receipts.

Public workload

Blender Cycles GPU rendering — $0.01 per completed frame.

Current public contract:

  • Workload: Blender Cycles GPU
  • Input: .blend
  • Execution: asynchronous
  • Output: downloadable artifact
  • Integrity: SHA-256 artifact verification
  • Evidence: FARPY execution receipt
  • Transparency: public proof surfaces
  • Status: LIVE_PUBLIC_ALPHA

Additional workloads are under development and are not currently public.

Agent / API access

Typical lifecycle:

discover → price → submit → JOB-ID → execute → download → verify receipt

Agent discovery

Public surfaces

Local MCP / Glama

A local stdio MCP server for Cursor, Claude Desktop, Glama, and other MCP clients lives in mcp/.

It is a thin public client over FARPY's existing Job API. It does not include production server code and never logs FARPY_AGENT_TOKEN.

Build and run
cd mcp
npm install
npm run build
npm test
node dist/mcp-server.js

Environment (see .env.example):

  • FARPY_AGENT_TOKEN — Job API farpy_agent_ key. Required for every tool. The server fails closed if it is missing.
  • FARPY_API_BASE — API origin. Default: https://api.farpy.com

Example local client config:

{
  "mcpServers": {
    "farpy": {
      "command": "node",
      "args": ["/absolute/path/to/farpy-public/mcp/dist/mcp-server.js"],
      "env": {
        "FARPY_AGENT_TOKEN": "farpy_agent_..."
      }
    }
  }
}

Public MCP V1 tools: inspect, quote, start, status, download, receipt. inspect and quote do not spend. start is the spend boundary and requires legal_acceptance=FARPY_LEGAL_V1.

Scope

FARPY is currently a public-alpha service.

Public capabilities, pricing, and limits are authoritative. Historical research, internal tests, and experimental workloads do not imply current public availability.

Frequently asked questions

What is io.github.Mangomunchr/farpy?

FARPY routes GPU workloads to qualified compute and returns verified artifacts and receipts.

How do I install io.github.Mangomunchr/farpy?

It runs as a remote server. In Claude Code: claude mcp add --transport http farpy 'https://api.farpy.com/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.

Does io.github.Mangomunchr/farpy need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is io.github.Mangomunchr/farpy open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains io.github.Mangomunchr/farpy?

It is published by Mangomunchr. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.