Context7 Mcp logo

Context7 Mcp

Community
danielvm-git
context7-mcp

Fetch current library docs via Context7 MCP instead of training data. Use when user asks about frameworks, APIs, setup, or code examples for React, Next.js, Prisma, etc.

Overview

Publisherdanielvm-git
Repositorybigpowers
Skill namecontext7-mcp
Stars
206
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by danielvm-git on GitHub. Read the source before you install it.

Installation

Install the Context7 Mcp AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/danielvm-git/bigpowers.git /tmp/bigpowers
mkdir -p .claude/skills
cp -r /tmp/bigpowers/skills/context7-mcp .claude/skills/context7-mcp
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Context7 Mcp in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Context7 Mcp on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Context7 Mcp is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Context7 MCP

HARD GATE — Max 3 Context7 tool calls per user question (resolve-library-id + query-docs count toward the cap). On quota/rate-limit errors, emit an explicit CONTEXT7_UNAVAILABLE block — do NOT silently answer from training data.

HARD GATE — Before HTTP fetch, check bash scripts/lib/doc-fetch-cache.sh get "<libraryId>:<query>". Cache hit within TTL → use cached body (no round-trip). On ETag mismatch after conditional refresh, replace cache entry.

When to Use

  • Setup/configuration questions ("How do I configure Next.js middleware?")
  • Code involving libraries ("Write a Prisma query for…")
  • API references ("What are the Supabase auth methods?")
  • User mentions specific frameworks (React, Vue, Svelte, Express, Tailwind, etc.)

Bounded Retry (max 3x)

AttemptAction
1resolve-library-id → pick best match
2query-docs with selected libraryId
3Retry query-docs once with refined query (narrower scope)

After 3 failures, stop and print:

CONTEXT7_UNAVAILABLE
Reason: <quota|rate-limit|no-match|timeout>
Action: Ask user to retry later, paste official docs URL, or run `bts docs <lib>`.
Do NOT substitute training-data answers without labeling them UNVERIFIED.

Fetch Cache (ETag-revalidated)

  1. Cache key: "<libraryId>:<normalized-query>" (lowercase, trimmed).
  2. Read: bash scripts/lib/doc-fetch-cache.sh get "<key>" — exit 0 → use cached body.
  3. Miss / stale: call query-docs; store via doc-fetch-cache.sh put.
  4. TTL: 300s default (DOC_CACHE_TTL). Stale entries refresh on next fetch; honor ETag when MCP returns it.

bts docs <lib> shares the same cache helper when invoked from this skill.

Process

  1. resolve-library-id with libraryName + full user query.
  2. Select match: name similarity, reputation, benchmark score; prefer version-specific IDs when user names a version.
  3. query-docs with libraryId + specific question (one concept per call).
  4. Answer using fetched docs; cite library/version when relevant.

Verify

→ verify: test -f scripts/lib/doc-fetch-cache.sh

Frequently asked questions

What does the Context7 Mcp AI skill do?

Fetch current library docs via Context7 MCP instead of training data. Use when user asks about frameworks, APIs, setup, or code examples for React, Next.js, Prisma, etc.

Why use Context7 Mcp on TypingMind?

Because you install it once and use it with any model. Context7 Mcp is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Context7 Mcp in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielvm-git/bigpowers/tree/main/skills/context7-mcp. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Context7 Mcp?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Context7 Mcp?

As many as you like. As long as a model supports skills, you can use Context7 Mcp with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Context7 Mcp AI skill free?

Yes. It is published on GitHub by danielvm-git under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇