Retrieve Sentry issues and debugging tools with MCP server for error analysis and troubleshooting
# mcp-server-sentry: A Sentry MCP server
A Model Context Protocol server for retrieving and analyzing issues from Sentry.io. This server provides tools to inspect error reports, stacktraces, and other debugging information from your Sentry account.
When using [`uv`](https://docs.astral.sh/uv/) no specific installation is needed. We will use [`uvx`](https://docs.astral.sh/uv/guides/tools/) to directly run *mcp-server-sentry*.
Alternatively you can install `mcp-server-sentry` via pip:
``` pip install mcp-server-sentry ```
After installation, you can run it as a script using:
``` python -m mcp_server_sentry ```
Add this to your `claude_desktop_config.json`:
<details> <summary>Using uvx</summary>```json "mcpServers": { "sentry": { "command": "uvx", "args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"] } } ``` </details>
<details> <summary>Using pip installation</summary>```json "mcpServers": { "sentry": { "command": "python", "args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"] } } ``` </details>
Add to your Zed settings.json:
<details> <summary>Using uvx</summary>```json "context_servers": [ "mcp-server-sentry": { "command": { "path": "uvx", "args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"] } } ], ``` </details>
<details> <summary>Using pip installation</summary>```json "context_servers": { "mcp-server-sentry": { "command": "python", "args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"] } }, ``` </details>
You can use the MCP inspector to debug the server. For uvx installations:
``` npx @modelcontextprotocol/inspector uvx mcp-server-sentry --auth-token YOUR_SENTRY_TOKEN ```
Or if you've installed the package in a specific directory or are developing on it:
``` cd path/to/servers/src/sentry npx @modelcontextprotocol/inspector uv run mcp-server-sentry --auth-token YOUR_SENTRY_TOKEN ```
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
Discover seamless cross-platform e-commerce link conversion and product promotion with Taobao MCP Service supporting Taobao JD and Pinduoduo integrations
Configure and run ORAS MCP Server easily with Docker and VS Code integration
APIs for extreme p-value calculations in R via Python using FastMCP and pyper integration
Integrate and manage Cloudera Machine Learning with Python APIs for jobs, models, experiments, and project management
Discover MCP agent strategies supporting Function Calling and ReAct via HTTP SSE streamable protocols
Real-time and historical cryptocurrency market data via MCP server supporting major exchanges and comprehensive analysis