Sentry
by modelcontextprotocol
Retrieving and analyzing issues from Sentry.io
What is Sentry
mcp-server-sentry: A Sentry MCP server
Overview
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.
Tools
get_sentry_issue
- Retrieve and analyze a Sentry issue by ID or URL
- Input:
issue_id_or_url
(string): Sentry issue ID or URL to analyze
- Returns: Issue details including:
- Title
- Issue ID
- Status
- Level
- First seen timestamp
- Last seen timestamp
- Event count
- Full stacktrace
Prompts
sentry-issue
- Retrieve issue details from Sentry
- Input:
issue_id_or_url
(string): Sentry issue ID or URL
- Returns: Formatted issue details as conversation context
Installation
Using uv (recommended)
When using uv
no specific installation is needed. We will
use uvx
to directly run mcp-server-sentry.
Using PIP
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
Configuration
Usage with Claude Desktop
Add this to your claude_desktop_config.json
:
"mcpServers": {
"sentry": {
"command": "uvx",
"args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
}
}
"mcpServers": {
"sentry": {
"command": "docker",
"args": ["run", "-i", "--rm", "mcp/sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
}
}
"mcpServers": {
"sentry": {
"command": "python",
"args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
}
}
Usage with Zed
Add to your Zed settings.json:
"context_servers": [
"mcp-server-sentry": {
"command": {
"path": "uvx",
"args": ["mcp-server-sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
}
}
],
"context_servers": {
"mcp-server-sentry": {
"command": "python",
"args": ["-m", "mcp_server_sentry", "--auth-token", "YOUR_SENTRY_TOKEN"]
}
},
Debugging
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
License
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.
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
What are MCP Servers?
MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.
Are MCP Servers secure?
Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.
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