context-engineering

Context Engineering provides an MCP server that connects your IDEs (Cursor, Claude Code, VS Code, and any MCP-compatible IDE) to a centralized AI-assisted context engine hosted at contextengineering.ai. The server enables AI agents to maintain a persistent understanding of your codebase, architecture, and established patterns across sessions. To get started, sign up at contextengineering.ai to generate your unique API key. Then configure your IDE to point to the hosted MCP endpoint and include your API key in the request headers. Once configured, you can generate documentation, PRDs, and implementation plans directly from your IDE, with the server leveraging its codebase analysis, pattern recognition, and feature planning AI to deliver consistent, high-quality outputs. The integration supports Cursor, Claude Code, and VS Code, and is designed to work with any MCP-compatible IDE via standard MCP transport.

Prerequisites:

• Node.js (v14+ recommended) and npm/yarn installed on your machine
• Access to the Context Engineering MCP endpoint (contextengineering.ai) and a generated API key

Installation steps:

1. Install Node.js and npm from https://nodejs.org/
2. Open your terminal and install the MCP client package globally via npx (no permanent installation required):
   • You can issue: npx -y bralca-context-engineering-mcp
   • This will fetch the client that can connect to the hosted MCP server
3. Set up your environment variables or configuration with your API key and base URL:
   • Create or edit a local environment file or pass variables in your shell: MCP_BASE_URL=https://contextengineering.ai/mcp MCP_API_KEY=your-access-key
4. Run the MCP client to start using the server features from your IDE, following the IDE-specific setup instructions in the README (Cursor, Claude Code, VS Code).

Notes:

• If you prefer a persistent local client, you can pin a version of the client package in your project and run it via npm scripts.
• The MCP server is hosted; installation primarily involves configuring the client to authenticate and connect to the remote endpoint.

Tips and common considerations:

• Ensure you keep your API key secure; never commit it to public repositories.
• If you encounter connectivity issues, verify MCP_BASE_URL and MCP_API_KEY are correctly set and that your network allows access to contextengineering.ai.
• The hosted MCP server analyzes your codebase via the connected IDE; make sure your project is accessible by the IDE and that the MCP integration has permission to read relevant files.
• For best results, use the recommended IDEs (Cursor, Claude Code, VS Code) with the provided setup guides in the README.
• You can customize the server usage by adjusting headers or parameters in your IDE configuration as described in the integration steps.