context7-intake

amit-sw's avatarfrom amit-sw

Use when Codex needs curated documentation context or outlines from the Context7 MCP server.

⭐0stars🔀0forks📁View on GitHub🕐Updated Dec 24, 2025
[Memory and Context Management]

When & Why to Use This Skill

The context7-intake skill is a specialized Claude tool designed to interface with the Context7 MCP server for intelligent documentation retrieval. It solves the critical challenge of context window limitations by providing multi-level summaries and curated outlines, allowing AI agents to access vast knowledge bases without performance degradation. By routing research tasks to a dedicated server, it ensures that only the most relevant, cited information is ingested into the active session, optimizing both token usage and response accuracy.

Use Cases

  • Technical Research: Quickly retrieve architecture overviews or service histories from large documentation repositories without manual searching.
  • Context Optimization: Use the 'outline-first' approach to preview large document collections and select only essential passages, preventing context window overflow and reducing latency.
  • Knowledge Curation: Automatically search, summarize, and cite specific sections from hosted collections to build a persistent local knowledge base for long-term projects.
  • Efficient Information Retrieval: Execute sequential, filtered searches across multiple documentation tags and collections to find precise answers for complex engineering or background research queries.
namecontext7-intake
descriptionUse when Codex needs curated documentation context or outlines from the Context7 MCP server.

Context7 Intake

Purpose

Route documentation and background research tasks to the Context7 hosted MCP server so Codex can retrieve multi-level summaries without overloading the context window.

Setup Checklist

  1. Confirm CONTEXT7_ENDPOINT and CONTEXT7_API_KEY are available plus optional CONTEXT7_COLLECTIONS.
  2. Update servers/context7/config.json when you add or remove collections so the metadata stays accurate.
  3. For large collections, request an outline first before pulling full passages.

Workflow

  1. Define the brief – specify what context is needed (e.g., “architecture overview for Scheduler service between 2022-2023”).
  2. Search – call the Context7 search tool with filters (collection, tags). If no hit, broaden keywords or switch collections.
  3. Summarize – use the server’s outline/summary tools, then refine by requesting the exact sections.
  4. Cite – capture the provided citation metadata when transferring insight into other skills or docs.

Notes

  • Context7 enforces concurrency quotas—queue multiple queries sequentially.
  • When multiple results are returned, prefer outlines first, then fetch full passages for the top 2 hits.
  • Store curated snippets in docs/context/ if they should be re-used later.