The MCP Server Directory
Every Model Context Protocol server, scored on reliability, documentation, maintenance, and adoption. Independent, opinionated, refreshed daily from the official registry.
What this is
The MCP Server Directory is a live, independently maintained index of Model Context Protocol servers published to the official registry. Each server is scored 0–10 on four dimensions: reliability, documentation quality, maintenance velocity, and adoption. The directory is free, updated daily, and built by MegaOne AI.
Dataxplan MCP
3.7/10Read PostgreSQL EXPLAIN plans for AI agents: bottlenecks, estimation errors, fixes, charts.
MCP Server
3.5/10Retrieve product specifications and technical details from Icecat's database
Rxradar
3.5/10Semantic search across 5 US government healthcare databases.
MCP Server
3.5/10Create, manage, and query your Google Cloud SQL resources.
MCP Server
3.5/10Official Airtable MCP server — database and operations layer for agents.
Darkweb Breach
3.5/10OSINT dark web database search tool detecting credential leaks.
Data Observability
3.5/10SQL data health analyzer and pipeline observability evaluator.
Datahealth Observer
3.5/10Database health auditor monitoring query latencies.
Mc Data Monitor
3.5/10SQL pipeline observability and DBT integration monitor.
Query Forge
3.5/10Enterprise SQL query optimizer and performance analyzer.
Serverless Db Oracle
3.5/10PostgreSQL database administrator with serverless query routing.
Inutriplan MCP
3.5/10MCP server exposing supplements database used by iNutriPlan.com
Read Only Mysql MCP Server
3.3/10MCP server for read-only MySQL database queries in Claude Desktop
Mssql Writer
3.3/10MCP server for Microsoft SQL Server — read and data write operations, no DDL
Postgres Connector
3.3/10MCP server for querying PostgreSQL databases
Cartographer MCP
3.3/10Rule-tiered AST and sqlite-vec capability oracle for A-MEM agent workflows.
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Four dimensions, weighted
- Reliability (30%) — repository present, permissive license, not archived, official status.
- Documentation (20%) — description length, website presence, README quality.
- Maintenance (25%) — how recently the code was pushed; versioning discipline.
- Adoption (25%) — GitHub stars (log-scaled), remote availability, official endorsement.
What is MCP?
MCP stands for Model Context Protocol. It is an open standard introduced by Anthropic in late 2024 that lets AI assistants like Claude connect to external tools, data sources, and services through a common interface. An MCP server is a small program that exposes one capability (file access, a database, an API) to any MCP-compatible AI client.
Where does the data come from?
Every server in this directory is pulled from the official Model Context Protocol Registry at registry.modelcontextprotocol.io. We also enrich each entry with GitHub metadata (stars, last commit, license, primary language) where a repository is linked. The full re-scan runs daily.
How are servers scored?
Each server gets a 0–10 overall score, weighted from four sub-scores: reliability (30%), documentation (20%), maintenance (25%), and adoption (25%). The full methodology is visible on this page under "How scoring works".
Is this affiliated with Anthropic?
No. MegaOne AI is independent. Anthropic created the MCP standard and maintains the reference implementations, but this directory is built separately and rates all servers including Anthropic's own.
How often does the directory update?
The pipeline re-fetches the full registry and re-scores every active server once per day. Individual entries are refreshed whenever a new version is published to the official registry.
Is it free?
Yes. Browsing, filtering, and searching the directory is free. The weekly email briefing is free. There is no account required.