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AI developers wiring tools and data sources into agents who want a vetted, install-ready index of Model Context Protocol servers instead of scattered GitHub repos
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MCPhq
MCPhq is a maintained directory for the Model Context Protocol ecosystem, built for developers who are wiring tools and data sources into AI agents and want to know which servers are actually worth installing. It tracks thousands of MCP servers and, crucially, does the part most lists skip: every entry carries a ready-to-copy install configuration, so getting a server running inside Claude Desktop, Cursor, or a custom agent runtime is a paste rather than a documentation hunt. Servers are ranked by adoption and maintenance signals rather than submission order, which surfaces the ones with real usage and recent commits ahead of abandoned experiments. Category views group servers by what they connect to — databases, browsers, file systems, SaaS APIs, developer tooling — and comparison pages put similar servers next to each other so you can pick between two Postgres or two GitHub integrations without reading both repos. Alongside the directory, MCPhq publishes ecosystem news and practical guides covering spec changes, new client support, and setup patterns. For anyone building agentic software in 2026, it functions as the package index the protocol does not yet have officially.
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Pros
- Ready-to-copy install configs remove the usual MCP setup friction
- Rankings weigh adoption and maintenance instead of submission recency
- Comparison pages help choose between overlapping servers quickly
- Category structure maps to what each server actually connects to
- Free to browse with no account required
Cons
- Value depends on how quickly new servers are indexed as the ecosystem moves
- Only useful if you are already building with MCP-compatible clients
- Quality signals are directory-level, not a substitute for reading a server's code
- No hosted execution — you still run every server yourself
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