ACE MCP Server

Agentic Context Engineering (ACE) - Self-improving AI context framework with Model Context Protocol (MCP) integration for Cursor AI.

🎯 Overview

ACE MCP Server is an intelligent development assistant that learns from your coding patterns and automatically enhances your development workflow. It integrates seamlessly with Cursor AI through the Model Context Protocol (MCP), providing contextual code generation, intelligent analysis, and self-improving recommendations.

✨ Key Features

• 🤖 Smart Code Generation - Context-aware code generation with automatic prompt enhancement

• 🧠 Intelligent Code Analysis - Deep code analysis with actionable improvement suggestions

• 📚 Self-Improving Playbook - Accumulates knowledge and patterns from your development work

• 🔧 Multiple LLM Support - Works with OpenAI, Anthropic Claude, DeepSeek, Google Gemini, Mistral, and LM Studio

• 🐳 Docker Ready - Complete containerized solution for local and production deployment

• 🔒 Secure by Default - Bearer token authentication and comprehensive security measures

🚀 What Makes ACE Special

ACE doesn't just generate code - it learns from your development patterns and improves over time:

1. Generates contextual development trajectories

2. Reflects on code to extract insights and patterns

3. Curates knowledge into a self-improving playbook

4. Enhances future interactions with accumulated wisdom

📚 Documentation

🚀 Getting Started

• Installation Guide - Complete setup instructions

• Project Overview - Detailed project introduction

• Quick Start - Fast track to running ACE

⚙️ Setup & Configuration

• Cursor AI Setup - Basic MCP integration

• Enhanced Auto Setup - Smart auto-enhancement features

• LLM Providers - Configure different AI providers

🚀 Deployment

• Production Deployment - Deploy to production servers

• Full Deployment Guide - Complete Docker deployment guide

📖 Project Documentation

• Project Status - Current development status

• Architecture - Technical architecture details

• GitHub Setup - Repository initialization

⚡ Quick Start

1. Clone and Setup

2. Docker Development

3. Configure Cursor AI

See detailed setup instructions:

• Basic Cursor AI Setup - Initialize your MCP server with basic ACE tools

• Enhanced Auto Setup - Automatically enhance prompts and invoke appropriate ACE methods

4. Use ACE Commands

5. View Playbook

The ACE playbook stores accumulated knowledge and patterns from your development work. View it using:

Option 1: Via API endpoint (JSON)

Option 2: Using provided script

Option 3: Via MCP tool in Cursor AI

Option 4: Via dashboard

The playbook contains:

• Patterns - Code patterns and conventions learned from your work

• Best Practices - Development best practices accumulated over time

• Insights - Key insights extracted from code reflections

🛠️ Development

Prerequisites

• Node.js 18+

• Docker & Docker Compose

• TypeScript

Local Development

Docker Management

🔧 Configuration

LLM Providers & Models

ACE supports 6 LLM providers with various models:

Supported Providers

1. DeepSeek (Recommended) ⭐

   • Provider: deepseek

   • Default Model: deepseek-chat (V3.2-Exp)

   • Embedding Model: deepseek-embedding

   • Best for: ACE framework performance, cost-effective

   • Pricing: $0.28/1M input, $0.42/1M output tokens

   • Context: 128K tokens, Max output: 32K (reasoner mode)

   • Environment Variables:

     LLM_PROVIDER=deepseek DEEPSEEK_API_KEY=sk-your-deepseek-api-key DEEPSEEK_MODEL=deepseek-chat DEEPSEEK_EMBEDDING_MODEL=deepseek-embedding

2. OpenAI

   • Provider: openai

   • Models: gpt-4o, gpt-4, gpt-3.5-turbo

   • Embedding Models: text-embedding-3-small, text-embedding-3-large

   • Environment Variables:

     LLM_PROVIDER=openai OPENAI_API_KEY=sk-your-openai-api-key OPENAI_MODEL=gpt-4o OPENAI_EMBEDDING_MODEL=text-embedding-3-small

3. Anthropic Claude

   • Provider: anthropic

   • Models: claude-3-5-sonnet-20241022, claude-3-opus, claude-3-sonnet, claude-3-haiku

   • Environment Variables:

     LLM_PROVIDER=anthropic ANTHROPIC_API_KEY=sk-ant-your-api-key ANTHROPIC_MODEL=claude-3-5-sonnet-20241022

4. Google Gemini

   • Provider: gemini

   • Models: gemini-1.5-pro, gemini-1.5-flash, gemini-pro

   • Environment Variables:

     LLM_PROVIDER=gemini GOOGLE_API_KEY=your-google-api-key GOOGLE_MODEL=gemini-1.5-pro

5. Mistral

   • Provider: mistral

   • Models: mistral-large-latest, mistral-medium-latest, mistral-small-latest

   • Environment Variables:

     LLM_PROVIDER=mistral MISTRAL_API_KEY=your-mistral-api-key MISTRAL_MODEL=mistral-large-latest

6. LM Studio (Local/Self-hosted)

   • Provider: lmstudio

   • Models: Any local model compatible with OpenAI API format

   • Environment Variables:

     LLM_PROVIDER=lmstudio LMSTUDIO_BASE_URL=http://localhost:1234/v1 LMSTUDIO_MODEL=local-model

Environment Variables

Copy .env.example to .env and configure:

For complete configuration options, see .env.example file.

🤝 Contributing

1. Read the Documentation - Start with Project Overview

2. Follow Best Practices - Review Development Guide

3. Submit PRs - Follow our contribution guidelines

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links

• GitHub Repository

• Issues & Bug Reports

• Documentation

ACE MCP Server - Making AI development smarter, one interaction at a time. 🚀