Developer Tools★★★★★5/5
Context7
Context7 solves the most common AI coding failure: outdated API suggestions. When you ask Claude about a library, it draws from training data that may be months or years old. Context7 intercepts that and fetches the actual current documentation at query time.
With 46k+ GitHub stars, it's the most popular individual MCP server in the ecosystem. Just add "use context7" to any prompt and it pulls version-specific docs for whatever library you're working with. Supports both remote (HTTP) and local (stdio) modes, with an optional free API key for higher rate limits.
This is the kind of tool that pays for itself in the first session. No more debugging hallucinated method signatures.
Pros
- + 46k+ GitHub stars — largest MCP server community
- + Solves a universal pain point: stale API docs from training data
- + Just add "use context7" to any prompt — zero workflow change
- + Both remote and local modes available
- + Free API key for higher rate limits
Cons
- - Coverage depends on which libraries are indexed — niche packages may be missing
- - Adds latency per query (fetches docs in real-time)
- - Quality of extracted docs varies by library
How We Use It
This gets the most daily use out of anything on this list. The nxsi.io stack touches Drizzle ORM, Hono, Next.js 14, and several other libraries that have had breaking changes between versions. Before Context7, Claude would consistently suggest Drizzle v0.28 patterns when we're on v0.30 — different migration syntax, different query builder API. Same with Hono middleware signatures.
Now it's just "use context7" appended to any prompt that involves a library. The Drizzle schema work for our 50-table database went noticeably faster once Claude was reading the actual current docs instead of guessing from training data. We also lean on it heavily when working with n8n's REST API, which has quirks that aren't well-represented in training data (the two API surfaces with different auth, for example).
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