SpecForge

SpecForge

SpecForge is a Model Context Protocol (MCP) server that connects an LLM client to a fully autonomous code-fixing pipeline. Point it at a GitHub issue, and it reads the repo, plans a fix, writes the code, tests it, and opens a pull request.

Category
Visit Server

README

SpecForge

Turn GitHub issues into merged pull requests — autonomously.

SpecForge is a Model Context Protocol (MCP) server that connects an LLM client (like Claude Desktop) to a fully autonomous code-fixing pipeline. Point it at a GitHub issue, and it reads the repo, plans a fix, writes the code, tests it, and opens a pull request — without a human touching the keyboard in between.

Built for the CyOps Arena x MiniMax M3 Hackathon 2025.


How It Works

SpecForge orchestrates four stages, each handled by a specialized agent:

Stage Agent What Happens
1. Recon Recon Agent Reads repo structure, detects language, package manager, and test runner
2. Plan Planning Agent Generates a file-level implementation plan from the issue description
3. Implement MiniMax M3 Writes the actual code changes
4. Review Review Agent Runs tests, self-critiques, and loops until the suite passes
5. Ship GitHub Agent Creates a branch, commits changes, and opens a pull request

You give it an issue URL. It gives you back a PR.


Prerequisites

Requirement Notes
Node.js v18 or higher
npm v9 or higher
CyOps account Free signup at ai.cysic.xyz
GitHub Personal Access Token Needs repo and pull_request scopes

Installation

1. Install dependencies

cd mcp-server
npm install
npm run build

2. Configure environment variables

cp .env.example .env

Edit .env with your credentials:

# GitHub — token needs repo, pull_requests, and contents (read + write) scopes
GITHUB_TOKEN=ghp_xxxxxxxxxxxxxxxxxxxx

# CyOps Gateway URL (from your ai.cysic.xyz workspace)
CYOPS_GATEWAY_URL=https://your-instance.cysic.xyz

# CyOps API key (Settings → API Keys, inside your workspace)
CYOPS_API_KEY=cyops_xxxxxxxxxxxxxxxxxxxx

3. Set MiniMax M3 as your model in CyOps

  1. Open your CyOps workspace and click Open Gateway
  2. Go to Settings → LLM Proxy
  3. Set each agent's model to MiniMax M3

This unlocks the hackathon's 80% discount on token pricing.

4. Connect to Claude Desktop

Open your Claude Desktop config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add SpecForge as an MCP server:

{
  "mcpServers": {
    "specforge": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-server/dist/index.js"]
    }
  }
}

Restart Claude Desktop. SpecForge should now appear in your available tools.


Usage

In Claude Desktop, just describe what you want fixed:

Use specforge to fix https://github.com/org/repo/issues/42

SpecForge runs the full pipeline and returns a pull request URL when finished. No further input required unless you want to check progress mid-run.


Available Tools

specforge_run

Kicks off the full pipeline for a given issue.

{
  issue_url: string;           // Required — full GitHub issue URL
  strategy_profile?: string;   // Optional — CyOps strategy (default: "Default RLCR (Claude → MiniMax M3)")
  max_wait_minutes?: number;   // Optional — timeout in minutes (default: 10)
}

specforge_status

Checks the status of an in-progress run.

{
  run_id: string;     // CyOps run ID, returned from specforge_run
  project_id: string; // CyOps project ID, returned from specforge_run
}

Architecture

specforge_run (MCP tool)
  │
  ├── parseIssueUrl()          → Parse the GitHub issue URL
  ├── fetchIssue()              → Read issue body + comments
  │
  ├── runRecon()                → Recon Agent
  │     ├── fetchRepoContext()
  │     ├── readFile() × N      → package.json, tsconfig, etc.
  │     └── detect test runner, package manager
  │
  ├── createProject()           → CyOps: create new project
  ├── generatePlan()            → CyOps: generate plan from requirement
  ├── startRun()                → CyOps: begin Implement → Review loop
  ├── pollRun()                 → CyOps: wait for completion
  │
  ├── getArtifacts()            → List changed files
  ├── readWorkspaceFile() × N   → Read each changed file
  ├── createBranch()            → GitHub: create new branch
  ├── commitFileToGitHub() × N  → GitHub: push each changed file
  └── openPullRequest()         → GitHub: open pull request

Project Structure

mcp-server/
├── src/
│   ├── index.ts              # MCP server entry point + tool handlers
│   ├── github.ts             # GitHub API client
│   ├── cyops.ts               # CyOps Gateway API client
│   └── agents/
│       ├── recon.ts          # Recon Agent — repo understanding
│       └── orchestrator.ts   # Main pipeline coordinator
├── package.json
├── tsconfig.json
└── README.md

Hackathon

CyOps Arena x MiniMax M3 — June 2025

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured