# Sentry MCP Server 🔍
A TypeScript implementation of a Sentry MCP (Modern Context Protocol) tool that allows AI agents to access and analyze Sentry error data. 🤖
## ✨ Features
- 🎯 Retrieve and analyze Sentry issues
- 📊 Get formatted issue details and metadata
- 🔬 View detailed stacktraces
- 🛠️ Support for both tool and prompt interfaces
- 🛡️ Robust error handling
- 🔄 Real-time communication
## 📦 Installation
```bash
pnpm install
```
## 🔧 Configuration
Create a `.env` file in the root directory with your Sentry auth token:
```env
SENTRY_AUTH_TOKEN=your_sentry_auth_token
SENTRY_API_BASE=https://sentry.io/api/0/ # Optional, defaults to this value
```
## 📚 Usage
### Starting the Server 🚀
```bash
pnpm build && pnpm start
```
The server will start on port 1337 by default.
### Using with MCP 🛠️
The server provides two MCP interfaces:
1. Tool Interface: `get_sentry_issue`
```json
{
"issue_id_or_url": "12345"
}
```
2. Prompt Interface: `sentry-issue`
```json
{
"issue_id_or_url": "https://sentry.io/organizations/your-org/issues/12345/"
}
```
## 💡 Integrating with Cursor IDE
The Sentry MCP Server can be integrated with Cursor IDE for enhanced development experience:
1. 🚀 Start the MCP server locally using `pnpm start`
2. 🔧 Configure Cursor to use the local MCP server:

3. 🎉 Enjoy seamless Sentry issue analysis directly in your IDE!
## 🤝 Contributing
1. 🔀 Fork the repository
2. 🌿 Create your feature branch
3. 💾 Commit your changes
4. 🚀 Push to the branch
5. 📬 Create a new Pull Request
MCP directory API
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/FaureAlexis/sentry-mcp-server'
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