An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.
Enables reproducible evaluation of AI coding agents by exposing repository inspection, code editing, test running, and deterministic verification through MCP tools.
A local MCP server that enables Codex and other MCP clients to orchestrate native external coding-agent harnesses through a normalized lifecycle, with guarded execution and deterministic testing.
MCP server for Codabench REST API that enables AI agents to drive a full participant ML-benchmark workflow: discover competitions, download data, submit, poll, and read leaderboards.