Sentry MCP Server
Sentry MCP servers enable AI models to interact with Sentry's error monitoring and performance tracking platform, providing capabilities for analyzing errors, tracking performance, and assisting in debugging applications.
Overview
The Sentry MCP Server enables AI models to interact directly with Sentry's error monitoring and performance tracking platform through the Model Context Protocol (MCP). It provides a standardized interface for error analysis, performance monitoring, and automated issue management while maintaining security and data privacy.
Official Server:
Developed and maintained by Sentry
Key Features
Error Tracking & Analysis
Access and analyze Sentry issues, errors, and stack traces.
Performance Monitoring
Monitor application performance data and identify bottlenecks.
Issue Management
Manage and resolve issues, including creating projects and DSNs.
AI-Assisted Debugging
Leverage AI for root cause analysis and automated fixes via Seer integration.
Available Tools
Quick Reference
| Tool | Purpose | Category |
|---|---|---|
find_projects | Find projects in an organization | Discovery |
search_issues | Search grouped issues in Sentry | Read |
get_issue_details | Get details for an issue by URL, issue ID, or event ID | Read |
create_project | Create a project and provision a DSN | Write |
Detailed Usage
find_projectsβΆ
Find projects in an organization.
use_mcp_tool({
server_name: "sentry",
tool_name: "find_projects",
arguments: {
organizationSlug: "your-organization-slug",
query: "checkout"
}
});
Returns up to 25 project slugs. When hasMore is true, narrow the results with query.
search_issuesβΆ
Search grouped issues with Sentry search syntax or a natural-language query.
use_mcp_tool({
server_name: "sentry",
tool_name: "search_issues",
arguments: {
organizationSlug: "your-organization-slug",
query: "is:unresolved level:error",
projectSlugOrId: "your-project-slug",
sort: "date"
}
});
Returns a list of grouped issues. Use it for lists, not counts or individual event details.
get_issue_detailsβΆ
Get detailed information about a specific Sentry issue.
use_mcp_tool({
server_name: "sentry",
tool_name: "get_issue_details",
arguments: {
issueUrl: "https://sentry.io/organizations/your-org/issues/12345/"
}
});
You can also pass organizationSlug with issueId or eventId.
create_projectβΆ
Create a new project in Sentry.
use_mcp_tool({
server_name: "sentry",
tool_name: "create_project",
arguments: {
organizationSlug: "your-organization-slug",
teamSlug: "your-team-slug",
name: "New Project Name",
platform: "javascript"
}
});
Returns the created project slug and a usable DSN when client key setup succeeds.
Installation
{
"mcpServers": {
"sentry": {
"command": "npx",
"args": [
"-y",
"@sentry/mcp-server@latest",
"--access-token",
"YOUR_SENTRY_TOKEN"
],
"env": {
"SENTRY_HOST": "your_sentry_host" // Optional, for self-hosted Sentry
}
}
}
}
Sentry Access Token:
Replace YOUR_SENTRY_TOKEN with a Sentry User Auth Token with appropriate scopes (org:read, project:read, project:write, team:read, team:write, event:write).
Sources
Related Articles & Guides
Accessibility Scanner MCP Server
Accessibility Scanner MCP servers enable AI models to perform WCAG compliance checks, capture annotated screenshots, and generate detailed accessibility reports.
Auth0 MCP Server
Auth0 MCP server enables AI models to interact with Auth0 identity and access management, including applications, APIs, actions, logs, and forms.
AWS MCP Server
Interact with Amazon Web Services through your AI assistant using the AWS API MCP Server.