Use Context7 MCP and project MCPs for live documentation in Claude Code

Problem

AI models have a knowledge cutoff and generate code based on training data that may be months or years old. When working with fast-moving frameworks (Next.js, Supabase, Convex, SvelteKit), the generated code often uses deprecated APIs, outdated patterns, or missing features. Pasting docs manually into context is tedious and eats up your context window.

// Claude generates Next.js 13 patterns when you're on Next.js 15
// e.g., using `getServerSideProps` instead of server components
export async function getServerSideProps() {
  // This pattern is outdated in Next.js 15 app router
}

Solution

Option 1: Context7 MCP for live framework documentation

Add Context7 to your MCP configuration to pull current library docs on demand:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Then reference it in your prompts:

use context7 to look up the latest Next.js app router docs for server actions,
then implement a form submission handler using the current API

Option 2: Stack project context MCPs for full awareness

Combine documentation MCPs with project knowledge sources:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    },
    "notion": {
      "command": "npx",
      "args": ["-y", "@notionhq/mcp-server"],
      "env": {
        "NOTION_API_KEY": "ntn_xxx"
      }
    },
    "linear": {
      "command": "npx",
      "args": ["-y", "@linear/mcp-server"],
      "env": {
        "LINEAR_API_KEY": "lin_api_xxx"
      }
    }
  }
}

Option 3: Use CLAUDE.md to enforce doc lookups

# CLAUDE.md
## Rules
- Before writing code for Next.js, Supabase, or Convex, ALWAYS use context7
  to fetch the latest documentation for the relevant API
- Reference Linear tickets for acceptance criteria before implementing features
- Check Notion project pages for architectural decisions

Why It Works

Context7 maintains an index of up-to-date documentation for popular libraries and serves it through MCP tools. Instead of relying on the model's training data, the AI fetches current docs at generation time. Layering project-specific MCPs (Notion for specs, Linear for tickets) gives the model full context about both the technology and your specific requirements, producing code that matches both the latest API and your project's conventions.

Context

• Context7 supports hundreds of libraries including React, Next.js, Supabase, Prisma, and Tailwind
• Stainless can auto-generate MCP servers from OpenAPI specs, keeping your own API docs available
• Google AI Studio offers 1M token context as an alternative for dumping large codebases with docs
• The combination of live docs + project context + coding rules (CLAUDE.md) creates a robust pipeline that minimizes hallucinated APIs
• MCP servers run locally, so documentation fetches do not send your code to third parties