MCP Sentry
Provides tools for retrieving and analyzing error reports from Sentry.io, including the ability to fetch detailed issue information, view stacktraces, and list issues by project to help with debugging and error monitoring.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Sentry show me the latest issues for my-api project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-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_issueRetrieve 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
get_list_issuesRetrieve and analyze Sentry issues by project slug
Input:
project_slug(string): Sentry project slug to analyzeorganization_slug(string): Sentry organization slug to analyze
Returns: List of issues with details including:
Title
Issue ID
Status
Level
First seen timestamp
Last seen timestamp
Event count
Basic issue information
Prompts
sentry-issueRetrieve issue details from Sentry
Input:
issue_id_or_url(string): Sentry issue ID or URL
Returns: Formatted issue details as conversation context
Related MCP server: MCP Server Sentry
Installation
Installing via Smithery
To install mcp-sentry for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @qianniuspace/mcp-sentry --client claudeUsing uv (recommended)
When using uv no specific installation is needed. We will
use uvx to directly run mcp-sentry.
Using PIP
Alternatively you can install mcp-sentry via pip:
pip install mcp-sentryor use uv
uv pip install -e .After installation, you can run it as a script using:
python -m mcp_sentryConfiguration
Usage with Claude Desktop
Add this to your claude_desktop_config.json:
"mcpServers": {
"sentry": {
"command": "uvx",
"args": ["mcp-sentry", "--auth-token", "YOUR_SENTRY_TOKEN","--project-slug" ,"YOUR_PROJECT_SLUG", "--organization-slug","YOUR_ORGANIZATION_SLUG"]
}
}"mcpServers": {
"sentry": {
"command": "docker",
"args": ["run", "-i", "--rm", "mcp/sentry", "--auth-token", "YOUR_SENTRY_TOKEN","--project-slug" ,"YOUR_PROJECT_SLUG", "--organization-slug","YOUR_ORGANIZATION_SLUG"]
}
}"mcpServers": {
"sentry": {
"command": "python",
"args": ["-m", "mcp_sentry", "--auth-token", "YOUR_SENTRY_TOKEN","--project-slug" ,"YOUR_PROJECT_SLUG", "--organization-slug","YOUR_ORGANIZATION_SLUG"]
}
}Usage with Zed
Add to your Zed settings.json:
For Example Curson
"context_servers": [
"mcp-sentry": {
"command": {
"path": "uvx",
"args": ["mcp-sentry", "--auth-token", "YOUR_SENTRY_TOKEN","--project-slug" ,"YOUR_PROJECT_SLUG", "--organization-slug","YOUR_ORGANIZATION_SLUG"]
}
}
],"context_servers": {
"mcp-sentry": {
"command": "python",
"args": ["-m", "mcp_sentry", "--auth-token", "YOUR_SENTRY_TOKEN","--project-slug" ,"YOUR_PROJECT_SLUG", "--organization-slug","YOUR_ORGANIZATION_SLUG"]
}
},"context_servers": {
"sentry": {
"command": "python",
"args": [
"-m",
"mcp_sentry",
"--auth-token",
"YOUR_SENTRY_TOKEN",
"--project-slug",
"YOUR_PROJECT_SLUG",
"--organization-slug",
"YOUR_ORGANIZATION_SLUG"
],
"env": {
"PYTHONPATH": "path/to/mcp-sentry/src"
}
}
},Debugging
You can use the MCP inspector to debug the server. For uvx installations:
npx @modelcontextprotocol/inspector uvx mcp-sentry --auth-token YOUR_SENTRY_TOKEN --project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUGOr 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-sentry --auth-token YOUR_SENTRY_TOKEN --project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUG or in term
npx @modelcontextprotocol/inspector uv --directory /Volumes/ExtremeSSD/MCP/mcp-sentry/src run mcp_sentry --auth-token YOUR_SENTRY_TOKEN
--project-slug YOUR_PROJECT_SLUG --organization-slug YOUR_ORGANIZATION_SLUG
Fork From
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.
Available Tools
2 toolsget_list_issuesA
Retrieve and analyze Sentry issues by project slug. Use this tool when you need to: - Investigate production errors and crashes - Access detailed stacktraces from Sentry - Analyze error patterns and frequencies - Get information about when issues first/last occurred - Review error counts and status
Inputs: project_slug, organization_slug.
get_sentry_issueA
Retrieve and analyze a Sentry issue by ID or URL. Use this tool when you need to: - Investigate production errors and crashes - Access detailed stacktraces from Sentry - Analyze error patterns and frequencies - Get information about when issues first/last occurred - Review error counts and status
Inputs: issue_id_or_url (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 2 tools
The two tools are essentially indistinguishable in purpose. Both descriptions are identical, listing the exact same use cases (investigate errors, access stacktraces, analyze patterns, get timing info, review counts). An agent would have no way to determine when to use get_list_issues versus get_sentry_issue since they appear to serve the same function.
Both tools follow a similar get_ prefix pattern, which provides some consistency. However, the naming is confusingly similar (get_list_issues vs get_sentry_issue) rather than clearly differentiated, and the verb-noun structure is mixed (list_issues vs sentry_issue).
With only 2 tools, this feels severely under-scoped for a Sentry integration. A production error monitoring system would typically need tools for creating issues, updating statuses, searching/filtering, accessing events, or managing projects. Two tools is too few to cover meaningful workflows.
The tool surface is severely incomplete for Sentry's domain. There are no tools for creating issues, updating issue status (resolve/ignore), searching across projects, accessing event details, managing alerts, or any administrative functions. The two existing tools appear redundant rather than complementary.
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