mcp-gauntlet is an evaluation framework designed to test MCP (Model Context Protocol) servers by determining if AI agents can actually accomplish meaningful tasks with the tools the server exposes. It runs agentic evaluations that include testing for capabilities like tool use and resistance to prompt injection. The package is aimed at developers building or validating MCP-compatible AI agent systems.
mcp-gauntlet is a LLM eval & observability product. It focuses on evaluating whether AI agents can successfully use tools provided by an MCP server to complete real tasks. mcp-gauntlet is an open-source project aimed at AI developers and researchers. The project is open source (MIT). It runs on the command line.
Ghaleb Dweikat builds and maintains mcp-gauntlet, and the product first shipped in 2026. The project is developed in the open on GitHub with 10 commits in the last 90 days. Among its 4 catalogued features are Agentic Evaluation, MCP Server Testing, and Tool Use Assessment. It exposes integrations via an MCP server.
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