MCP Server

@dimahike

Basic information

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.

MCP Server 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

MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

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

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.

Comments

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