# Mcp Rest Adapter

> 🚀 MCP REST Adapter - Bridge any REST API to AI agents (Claude, GPT-4) without code changes. Auto-generates AI tools from OpenAPI specs. Zero-config microservice integration for Model Context Protocol.

- **Type:** MCP server
- **Install:** `agentstack add mcp-deepwissen-mcp-rest-adapter`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [deepwissen](https://agentstack.voostack.com/s/deepwissen)
- **Installs:** 0
- **Category:** [Integrations](https://agentstack.voostack.com/c/integrations)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [deepwissen](https://github.com/deepwissen)
- **Source:** https://github.com/deepwissen/mcp_rest_adapter

## Install

```sh
agentstack add mcp-deepwissen-mcp-rest-adapter
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# MCP → REST Adapter

Make your existing REST APIs instantly accessible to AI agents (Claude, GPT-4, etc.) without changing a single line of code.

## 🚀 Quick Start (5 minutes)

```bash
# Clone the repository
git clone https://github.com/deepwissen/mcp_rest_adapter.git
cd mcp_rest_adapter

# Start everything with one command
./quick_start.sh
```

That's it! Your REST APIs are now AI-accessible. Test it:

```bash
curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "method": "tools/list", "params": {}, "id": 1}'
```

## 🎯 What This Does

The MCP Adapter acts as a bridge between AI agents and your existing microservices:

```
AI Agent (Claude/GPT) → MCP Protocol → MCP Adapter → Your REST APIs
```

**Before**: Months of custom AI integration code  
**After**: 5 minutes to AI-enable your entire API ecosystem

## 🛠️ Manual Setup

### Prerequisites
- Docker & Docker Compose
- Python 3.11+
- Your REST APIs with OpenAPI/Swagger specs

### Step 1: Configure Your Services

Edit `docker-compose.yml` to point to your services:

```yaml
environment:
  - CUSTOMER_SERVICE_URL=http://your-customer-api:8080
  - ORDER_SERVICE_URL=http://your-order-api:8080
  - INVENTORY_SERVICE_URL=http://your-inventory-api:8080
```

### Step 2: Start the Adapter

```bash
# Start with Docker Compose
docker-compose up -d

# Or run directly with Python
pip install -r requirements.txt
python -m uvicorn mcp_adapter.server:app --port 8000
```

### Step 3: Verify It's Working

```bash
# Check health
curl http://localhost:8000/health

# List available tools (auto-generated from your APIs)
curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "method": "tools/list", "params": {}, "id": 1}'
```

## 📋 Requirements for Your APIs

Your REST APIs need:
1. **Health endpoint** (`/health`) that returns 200 OK
2. **OpenAPI spec** (`/openapi.json` or `/swagger.json`)
3. **Standard REST patterns** (GET, POST, PUT, DELETE)

That's it. No code changes required.

## 🔧 Configuration

Create a `config.py` file:

```python
SERVICE_CONFIGS = {
    "customer": {
        "base_url": "http://customer-service:8001",
        "health_endpoint": "/health",
        "openapi_endpoint": "/openapi.json"
    },
    "order": {
        "base_url": "http://order-service:8002",
        "health_endpoint": "/health",
        "openapi_endpoint": "/openapi.json"
    }
}
```

## 🧪 Testing

Run the test suite:

```bash
# Run all tests
./run_tests.py

# Run with Docker
docker-compose -f docker-compose.test.yml up
```

## 📊 What You Get

Once running, AI agents can:
- Discover all your API endpoints automatically
- Call any endpoint with proper parameters
- Handle complex workflows across multiple services
- Get structured responses in MCP format

Example: An AI agent can now say "Show me all orders for customer John Doe" and automatically:
1. Search for the customer
2. Get their customer ID
3. Fetch all orders
4. Return formatted results

## 🚨 Troubleshooting

**Services not discovered?**
- Check your services have `/health` endpoints returning 200 OK
- Verify `/openapi.json` is accessible

**No tools generated?**
- Ensure your OpenAPI spec is valid
- Check logs: `docker-compose logs mcp-adapter`

**Connection errors?**
- Verify network connectivity between adapter and your services
- Check service URLs in configuration

## 🤝 Contributing

We welcome contributions! Please check out our [Contributing Guide](CONTRIBUTING.md).

## 📝 License

MIT License - see [LICENSE](LICENSE) file for details.

## 🔗 Links

- [Documentation](https://github.com/deepwissen/mcp_rest_adapter/wiki)
- [Issues](https://github.com/deepwissen/mcp_rest_adapter/issues)
- [Discussions](https://github.com/deepwissen/mcp_rest_adapter/discussions)

---

**Built with ❤️ to make AI integration simple**

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [deepwissen](https://github.com/deepwissen)
- **Source:** [deepwissen/mcp_rest_adapter](https://github.com/deepwissen/mcp_rest_adapter)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** yes
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-deepwissen-mcp-rest-adapter
- Seller: https://agentstack.voostack.com/s/deepwissen
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.