MCP server for AI Coding Gym - fetch and submit coding challenges
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"ai-coding-gym-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# AI Coding Gym - MCP Server Local MCP server for interacting with the AI Coding Gym platform. Provides tools to fetch coding problems and submit solutions. ## Features - **`/fetch`**: Fetch a coding problem and clone the repository to your local machine - **`/submit`**: Submit your solution by committing and pushing changes ## Quick Start ### Installation **Option 1: Install from PyPI** ```bash pip install ai-coding-gym-mcp ``` **Option 2: Install from GitHub** ```bash pip install git+https://github.com/yourusername/ai-coding-gym-mcp.git ``` **Option 3: Install from source** ```bash git clone https://github.com/yourusername/ai-coding-gym-mcp.git cd ai-coding-gym-mcp pip install -e . ``` ### Configure Claude Desktop Add to your Claude Desktop config (`~/Library/Application Support/Claude/claude_desktop_config.json` on Mac): ```json { "mcpServers": { "ai-coding-gym": { "command": "ai-coding-gym-mcp" } } } ``` ### Configure VS Code (Copilot with MCP) Add to your VS Code settings (`.vscode/settings.json` or User Settings): ```json { "github.copilot.chat.codeGeneration.instructions": [ { "text": "Use AI Coding Gym MCP tools for problem solving" } ], "mcp.servers": { "ai-coding-gym": { "command": "python", "args": ["-m", "server"], "cwd": "/path/to/ai-coding-gym-mcp" } } } ``` Or if installed via pip, use the executable directly: ```json { "mcp.servers": { "ai-coding-gym": { "command": "ai-coding-gym-mcp" } } } ``` ## Usage ### Running the MCP Server The server uses stdio for communication with MCP clients: ```bash python server.py ``` Or configure it in your MCP client settings (e.g., Claude Desktop). ### Tool: `/configure` Configure the MCP server with your user ID. This generates an SSH key pair and registers it with the server. **Parameters:** - `user_id` (required): Your user ID for authentication - `workspace_dir` (required): Default workspace directory for …
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.