Context7 MCP. Stop Guessing API Versions. Use Live Docs.
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Context7 instantly grounds your AI agent in accurate technical documentation. It resolves fuzzy framework names—like 'react' or 'tailwind'—into specific, version-controlled paths, letting your agent pull up-to-date API signatures and working code examples directly into your workflow.
What your AI agents can do
Query docs
Retrieves detailed documentation and working code examples for a specific library topic.
Resolve library
Finds the exact, deterministic path and latest version number for any given framework or library.
It resolves general framework names into precise, versioned identifiers needed for deep documentation fetching.
You can query documentation on a niche topic and pull raw text chunks detailing the exact usage of a variable or function.
The agent pulls complete, functional code snippets for components or functions directly into your development context.
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Supported MCP Clients
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Context7: 2 Tools
These tools let you find the precise paths for frameworks and query detailed, version-specific documentation chunks.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Context7 on Vinkius019d757bquery docs
Retrieves detailed documentation and working code examples for a specific library topic.
019d757bresolve library
Finds the exact, deterministic path and latest version number for any given framework or library.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Context7, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Context7. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 2 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Debugging Code Context Is a Pain Point
Right now, when you hit an API snag, the process is brutal. You open your IDE, then jump to Google, hoping the search result points to the right documentation page. Then you have to manually navigate through versioning notes and outdated examples just to find a clean code snippet that actually works with your local stack.
With this MCP, the whole thing stays contained. Your agent figures out the exact library path, then pulls the raw, current Markdown chunk detailing the function signature and providing a ready-to-use code example. The context you need arrives directly into your workflow.
Get Accurate Code Context With `query_docs`
You stop manually cross-referencing multiple tabs and documentation sites. You no longer have to guess if an API signature changed between major releases; the MCP finds it for you.
The difference is massive: instead of spending 15 minutes trying to reconcile a deprecated function with current best practices, you get the correct code block in seconds.
What you can do with this MCP connector
You need your AI client to know the exact API signature for a component you built three years ago. Context7 handles that ambiguity. Instead of relying on generalized knowledge—which often means outdated or hallucinated data—this MCP pulls version-specific documentation from major libraries and frameworks. It first figures out the precise path for any framework, then uses that context to pull raw Markdown chunks detailing specific variables and functional code examples.
This process lets your agent talk to living, breathing API docs, so it never gets stuck on an obsolete function name. Because this MCP handles highly sensitive, version-specific codebase details, you know those credentials pass through a zero-trust proxy in Vinkius; they're used only for transit and never sit on disk.
You can chain this with other services to build complex automation pipelines that actually work across your entire stack.
019d757b-5f19-7054-8c59-dd260d3c4d66 
How Context7 MCP Works
- 1 First, ask the MCP to determine the correct library ID and latest version for a framework (like 'nextjs').
- 2 Next, use that precise identifier to query documentation about a specific topic or feature.
- 3 The agent receives raw Markdown chunks containing accurate code examples and API references.
The bottom line is your AI client stops guessing; it reads the official docs before generating anything.
Who Is Context7 MCP For?
This MCP saves time for senior developers, technical architects, and engineers who hate fighting outdated documentation. If you spend half your day searching Stack Overflow for an API signature that changed last month, you need this.
Uses it to pull accurate code examples for components in React or Tailwind CSS without leaving the IDE.
Grounds coding agents in real-time technical docs, drastically improving the accuracy of generated API calls.
Quickly verifies version-specific API signatures and cross-references documentation blocks against live data.
What Changes When You Connect
- Accurate Context: Instead of general knowledge, the agent uses
query_docsto fetch raw Markdown documentation chunks, guaranteeing you're working with technical truths. - Version Control: The
resolve_librarytool forces precision, turning vague framework names into specific paths (e.g., /react/18.2.0), eliminating version guesswork entirely. - Code Snippets: You pull valid code examples straight out of the documentation flow, skipping manual copy-pasting and boilerplate setup.
- Up-to-Date Knowledge: The MCP bypasses standard LLM training cutoffs by pulling data synchronized with the absolute latest library releases.
- Developer Focus: It keeps complex context retrieval inside your IDE or agent workflow, meaning you don't have to switch between documentation sites and code editors.
Real-World Use Cases
Building a Next.js Feature
A developer needs to know the exact structure for the 'App Router' in Next.js 14. They run resolve_library first, get the specific version ID, and then use that ID with query_docs to pull detailed Markdown segments showing exactly how to implement the layout.js and page.js structures.
Integrating a New Component
A rapid prototyper needs to know how to structure a new UI component using Tailwind CSS v4. They use resolve_library for the current version, then query documentation via query_docs to pull the precise code examples needed to implement it correctly.
Debugging Legacy Code
A technical writer needs to verify an API signature from a React component that hasn't been touched in years. They use the MCP to find the specific version path and then query documentation, verifying against the source of truth rather than memory.
Setting up a New Project Stack
An AI engineer is setting up an agent pipeline that requires multiple dependencies. They run resolve_library for every framework mentioned to ensure their code generation agent uses the correct, deterministic path for each library.
The Tradeoffs
Assuming the version
Asking your agent to write a React component without first verifying if the required API signature exists in the current framework version.
→
Always run resolve_library first. This guarantees you have the correct path, which then lets query_docs pull documentation based on that specific version.
Copying old examples
Finding an example online (e.g., GitHub) that works but uses outdated syntax or deprecated methods.
→
Use the MCP to retrieve code samples directly from official documentation via query_docs. This ensures the snippet is compatible with your resolved library version.
Vague framework search
Just asking, 'How do I use Next.js?' which yields a massive, unhelpful chunk of general theory.
→
First, run resolve_library to nail down the version. Then, specify the topic when calling query_docs, like 'App Router' or 'data fetching hook'.
When It Fits, When It Doesn't
Use this MCP if your job requires absolute accuracy regarding API signatures and dependency versions. If you need to write code that interacts with a specific library (React, Next.js, etc.), run the resolve_library tool first. This confirms the exact version path; without it, any documentation query is shot in the dark. Don't use this if your problem is general system design or high-level architecture—you need a different kind of knowledge base for that. But if you just need to know what color button to put on a page, this MCP won't help.
Common Questions About Context7 MCP
Can my agent find the latest documentation for a specific Tailwind CSS version? +
Yes. First, use the 'resolve_library' tool with 'tailwindcss'. It will return the deterministic ID and version (e.g., 'tailwindcss/3.4.1'). Then, use 'query_docs' to pull the exact Markdown blocks for your specific topic.
Does Context7 provide code examples for the libraries I search for? +
Absolutely. When you query documentation via the 'query_docs' tool, the agent retrieves not only textual descriptions but also version-specific code examples found in the original library documentation to ensure implementation accuracy.
How does this help prevent AI hallucinations in coding tasks? +
Standard LLMs have a training data cutoff. Context7 pulls live, version-specific documentation chunks that act as ground-truth context. By grounding your agent in this real-time data, it avoids hallucinating outdated or non-existent API methods.
How is my Context7 API Key managed when using the `resolve_library` tool? +
Your API Key is handled via a zero-trust proxy, ensuring it's only used in transit. The key never gets stored on any disk during your session with your agent.
What happens if I provide an ambiguous or misspelled name when calling `resolve_library`? +
The tool is designed to handle ambiguity. If the input is unclear, it returns a list of potential matches and asks you which specific ID (e.g., 'react' vs. 'next') you need to continue.
Are there rate limits when I use `query_docs` repeatedly in one session? +
While Vinkius handles the underlying infrastructure, standard API usage applies. We recommend batching your documentation queries or utilizing our token optimization features to keep costs and call volumes efficient.
Does `query_docs` pull only basic function signatures, or can it handle architectural concepts? +
The tool retrieves raw Markdown chunks from the official docs. This means you get detailed explanations of complex topics, not just simple API calls. You'll get deep context.
If I use an old version ID in `resolve_library`, will `query_docs` still work? +
Yes. Since the tool resolves deterministic paths for specific versions, you can query documentation for any older release as long as that documentation exists in Context7's indexed knowledge base.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.