UniversalBench

This is a managed runtime that moves Python execution, web search, database queries, and API calls outside your LLM context. Instead of your model processing raw data or writing untested code, UniversalBench runs the work in an isolated sandbox and returns only the final result. It enforces hard limits on cost per request, blocks private IP access, and validates code syntax before GitHub commits. You connect one MCP endpoint to Claude or any compatible client, and it handles GitHub operations, PostgreSQL queries, LLM routing, and general code execution. The pitch is token reduction through pre-computation rather than exposing tools for the model to reason over. Free tier includes 1,000 executions monthly.