MCP server for Context7

MCP server for Context7 is an application that provides AI assistants
with access to up-to-date library and framework documentation and code examples
via the standard Model Context Protocol (MCP).
The server is deployed on a virtual machine in Yandex Cloud.

Key Features and Benefits

• Yandex AI Studio Integration. The MCP server integrates with AI Studio MCP Servers — connect it to your AI agents in just a few clicks.
• Up-to-Date Documentation. Context7 provides AI assistants with access to fresh library and framework documentation, eliminating the problem of outdated model knowledge.
• Code Examples. In addition to documentation, the server returns relevant code examples for the requested libraries.
• AI Assistant Integration. Enables Claude, ChatGPT, and other AI models to retrieve contextual library information during their workflow.
• Bearer Token Authorization. All requests to the MCP server are protected with a Bearer token stored in Yandex Lockbox.
• Standard MCP Protocol. Uses the open Model Context Protocol for AI model interaction, ensuring compatibility with a wide range of clients.
• HTTP Transport. The MCP server is accessible on port 8000 (HTTP), simplifying integration with various clients and tools.
• Minimal Resources. The application runs on a virtual machine with minimal configuration (2 vCPU, 2 GB RAM), reducing infrastructure costs.
• Docker Containerization. The server runs in Docker containers (MCP + nginx auth proxy).

1. Create a secret in Yandex Lockbox to store the Bearer token for authorization. The secret must contain a bearer_token key with an arbitrary token value.
2. Create a service account with the roles compute.editor, iam.serviceAccounts.admin, lockbox.payloadViewer, vpc.admin (the admin role includes all the specified roles).
3. In the management console select the Cloud Apps service.
4. In the left panel, select Application Store.
5. Select MCP Context7 and click the Use button.
6. Specify:
   • Application name.
   • (Optional) Application description.
   • The service account created earlier.
   • The cloud subnet where the virtual machine will be deployed.
   • Lockbox secret ID containing the Bearer token for authorization.
7. Click the Install button and wait for the application to install.
8. After installation, the MCP server will be available at http://<vm-ip>:8000.
9. Configure your AI client (Claude Desktop, Cursor, etc.) to connect to the MCP server, specifying the Authorization: Bearer <your-token> header.

• Retrieving up-to-date documentation for libraries and frameworks (React, Next.js, LangChain, etc.) using an AI assistant.
• Searching for code examples for specific libraries via natural language.
• Eliminating the problem of outdated AI model knowledge when working with new library versions.
• Automatically obtaining contextual information about project dependencies.

Yandex Cloud technical support is available 24/7. The types of requests you can submit and the appropriate response time depend on your pricing plan. You can switch to the paid support plan in the management console. You can learn more about the technical support terms here.