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MCP Server

@dimahike

About MCP Server

A middleware server that acts as a bridge between Cursor IDE and AI models, validating AI responses using project context and Gemini.

Config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

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Overview

What is MCP Server?

MCP Server is a middleware server that acts as a bridge between Cursor IDE and AI models, validating AI responses using project context and the Gemini API. It is intended for developers using Cursor IDE who want to ensure AI-generated code or suggestions are consistent with their project’s context.

How to use MCP Server?

Clone the repository, install dependencies with npm install, create a .env file with your Gemini API key and configuration options, build the project with npm run build, and start the server with npm start. For development with hot-reloading use npm run dev. A local deployment script (./scripts/deploy-local.sh) is also provided for streamlined setup.

Key features of MCP Server

  • Project context management
  • AI response validation
  • Integration with Gemini API
  • Real‑time context updates
  • Comprehensive logging system
  • Easy local deployment

Use cases of MCP Server

  • Validate AI responses against current project context
  • Manage real‑time context updates inside Cursor IDE
  • Bridge Cursor IDE with Gemini‑powered AI models

FAQ from MCP Server

What are the prerequisites for MCP Server?

Node.js v14+ recommended, npm or yarn, a Google Cloud account for Gemini API access, a Gemini API key, and Cursor IDE.

How do I obtain a Gemini API key?

The README does not detail how to obtain the key, but it states you need a Google Cloud account and a Gemini API key to use the server.

How do I deploy the server locally?

Use the provided script ./scripts/deploy-local.sh, which checks for a .env file, installs dependencies, builds the project, and starts the server in production mode. Alternatively follow the manual steps: npm install, npm run build, npm start.

What API endpoints does MCP Server expose?

GET /api/health for health checks, POST /api/context/initialize and /api/context/refresh for context management, and POST /api/validate and /api/cursor/validate for AI response validation.

Where are server logs stored?

Logs are saved in the logs/ directory, as shown in the project structure.

Frequently asked questions

What are the prerequisites for MCP Server?

Node.js v14+ recommended, npm or yarn, a Google Cloud account for Gemini API access, a Gemini API key, and Cursor IDE.

How do I obtain a Gemini API key?

The README does not detail how to obtain the key, but it states you need a Google Cloud account and a Gemini API key to use the server.

How do I deploy the server locally?

Use the provided script `./scripts/deploy-local.sh`, which checks for a `.env` file, installs dependencies, builds the project, and starts the server in production mode. Alternatively follow the manual steps: `npm install`, `npm run build`, `npm start`.

What API endpoints does MCP Server expose?

GET `/api/health` for health checks, POST `/api/context/initialize` and `/api/context/refresh` for context management, and POST `/api/validate` and `/api/cursor/validate` for AI response validation.

Where are server logs stored?

Logs are saved in the `logs/` directory, as shown in the project structure.

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