Who benefits from using MCP Doctor?

It's for developers building MCP servers, aiming to ensure their tools are high-quality, discoverable, and usable by diverse audiences, including humans and AI agents.

Can AI agents use MCP Doctor directly?

Yes, MCP Doctor functions as an MCP server itself, enabling AI agents to use its `check_server` tool for automated evaluation of other MCP servers, integrating seamlessly into agent workflows.

How does MCP Doctor help improve server quality?

It provides actionable recommendations based on its comprehensive evaluation, helping developers address identified gaps and enhance their server's 'contract quality' and readiness.

Doctor

Name: Doctor
Author: Jiansen

byJiansen

0•

API 개발

개발자 도구

보안 및 테스팅

Checks and improves the contract quality of any MCP server, ensuring it satisfies distribution platforms, human users, and AI agents.

MCP Doctor addresses the common oversight of MCP servers being built primarily for human developers. It ensures that servers satisfy three critical audiences simultaneously: distribution platforms (which need structured metadata), human users (who require clear purpose, trust signals, and low install friction), and AI agents (who demand unambiguous tool descriptions and token-efficient responses). By evaluating six key dimensions of 'contract quality,' MCP Doctor provides actionable recommendations to enhance a server's overall quality and readiness for a diverse ecosystem, ultimately improving its parseability and utility across different platforms and users.

주요 기능

010 GitHub stars

02Generates output in various formats, including terminal, JSON for CI/CD, and Markdown for reports.

03Provides actionable recommendations to improve server 'contract quality' and readiness.

04Evaluates server quality across six dimensions: Task Clarity, Trust & Safety, Interface Quality, Token Efficiency, Install Friction, and Cross-platform Readiness.

05Functions as both a command-line interface (CLI) tool and an MCP server, allowing AI agents to use it for server evaluation.

06Supports both rule-based (offline) and AI-enhanced (LLM-driven) evaluation modes.

사용 사례

01Integrating into CI/CD pipelines to automate contract quality checks and ensure compliance.

02AI agents using the tool to evaluate other MCP servers for optimal integration and secure usage.

03Developers validating the quality and readiness of their MCP servers for deployment and agent interaction.