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AI Skill & MCP Quality Evaluation API
An API and platform that automatically benchmarks, tests, and ranks AI tools (MCPs) for reliability, providing a curated routing layer for complex multi-agent systems.
Por qué es importante
You are building a complex AI workflow and need to connect it to external services. You are faced with repositories containing hundreds of thousands of unverified skills and plugins. Instead of confidently deploying your agent, you spend hours manually testing tools because a failure deep in an autonomous pipeline breaks everything. Existing semantic search only matches tool descriptions, leaving you completely blind to whether the tool actually executes reliably in practice.
- · Creado para Developers building multi-agent orchestrators and enterprise AI teams needing reliable tool execution..
- · Monetización más probable: SaaS subscription / API usage based.
El Dolor · Narrativa
You are building a complex AI workflow and need to connect it to external services. You are faced with repositories containing hundreds of thousands of unverified skills and plugins. Instead of confidently deploying your agent, you spend hours manually testing tools because a failure deep in an autonomous pipeline breaks everything. Existing semantic search only matches tool descriptions, leaving you completely blind to whether the tool actually executes reliably in practice.
Desglose de puntuación
Señal de Mercado
Estrategia de lanzamiento
AI engineers and technical founders building agentic workflows using LangChain or custom orchestration.
~25,000 highly active developers globally
Hacker News launch focused on the 'AI tool garbage' problem
$49/month for API access to curated tool metrics
100 developers integrating the API to route their agent tool calls
Alcance del MVP · 1-2 semanas
- Scrape top 500 most popular open-source MCP servers/tools
- Define a standard JSON schema for evaluating tool inputs and outputs
- Write a Python script to execute basic generic prompts against these 500 tools
- Log success rates, failure reasons, and response latencies into a PostgreSQL database
- Build a simple REST API endpoint that returns the top 10 most reliable tools by category
- Develop a lightweight landing page explaining the 'quality over quantity' problem
- Create an SDK wrapper for easy integration into LangChain/Python workflows
- Implement a daily cron job to re-test the top 500 tools and update database metrics
- Add a 'request verification' form for tool creators to submit their own tools
- Launch the initial API to a closed group of developer communities for feedback
Diferenciación
Por qué esto podría fallar
Autorrefutación: la señal de confianza más importante
- 1The continuous compute required to accurately test thousands of tools via LLMs will bankrupt the project before it achieves scale.
- 2Major players like OpenAI or Anthropic will introduce strict, verified tool marketplaces, instantly killing third-party curation needs.
- 3Developers may prefer to write their own brittle, hard-coded integrations rather than pay for a dynamic routing API.
Resumen de evidencia
Cómo la IA sintetizó esta información: sin citas textuales
Multiple commenters expressed deep skepticism regarding claims of having hundreds of thousands of available skills. They specifically noted that matching algorithms based purely on vector similarity cannot guarantee functional quality, creating a critical bottleneck where bad tool selection collapses complex agentic workflows.
Plan de Acción
Valida esta oportunidad antes de escribir código
Próximo Paso Recomendado
Construir
Señales de demanda fuertes. Hay dolor real y disposición a pagar — empieza a construir un MVP.
Kit de Textos para Landing Page
Textos listos para pegar, basados en el lenguaje real de la comunidad de Reddit
Titular
AI Skill & MCP Quality Evaluation API
Subtítulo
An API and platform that automatically benchmarks, tests, and ranks AI tools (MCPs) for reliability, providing a curated routing layer for complex multi-agent systems.
Para Quién Es
Para Developers building multi-agent orchestrators and enterprise AI teams needing reliable tool execution.
Lista de Funciones
✓ Automated unit testing for public MCP servers ✓ Reliability scoring API (uptime, latency, hallucination rate) ✓ Semantic search augmented with quality metrics ✓ Fallback routing logic when primary tools fail
Dónde Validar
Comparte tu landing page en r/Product Hunt · artificial-intelligence — ahí es exactamente donde se descubrieron estos puntos de dolor.
Regístrate para desbloquear el análisis profundo completo
GTM, alcance del MVP, por qué podría fallar, ActionPlan Copy Kit. El registro gratuito otorga 10 vistas detalladas/mes.
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