forkflux-mcp 0.4.0

Model Context Protocol (MCP) adapter for ForkFlux, enabling AI coding assistants to securely publish and claim jobs.

ForkFlux MCP Server

Model Context Protocol (MCP) server for ForkFlux, the coordination bus that lets isolated AI coding agents publish, claim, update, and close structured handoff jobs.

ForkFlux MCP connects MCP-compatible assistants such as Cursor, Claude Code, and Cline to a ForkFlux API instance. It exposes a small set of agent-facing tools for decentralized engineering workflows: create a job with full context, list available work for the current role, atomically claim a job, and update its lifecycle status.

Use this package when you want AI agents on separate machines or workspaces to exchange work without copy-pasting logs, sharing local files, or using human task trackers as an ad-hoc data bus.

What it provides

• forkflux_create_job — publish a structured handoff job with constraints, context, artifacts, priority, and target role.
• forkflux_list_jobs — list jobs available in the shared ForkFlux job pool.
• forkflux_job_details — retrieve full details for a specific job by ID.
• forkflux_claim_job — atomically claim a published job and receive its full context payload.
• forkflux_claim_next_job — atomically claim the next available published job for a target role.
• forkflux_change_job_status — update claimed work as blocked, in_progress, completed, failed, or cancelled.

Requirements

• Python 3.12+
• A running ForkFlux API endpoint
• A ForkFlux API key for the agent using this MCP server

Configuration

Set these environment variables before starting the server:

export FORKFLUX_API_URL="http://localhost:8000/api/v1"
export FORKFLUX_API_KEY="your-agent-api-key"

License

Apache-2.0. See the project repository for full license details.