A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.
This is a Model Context Protocol (MCP) server implemented in TypeScript for connecting to the Sentry error tracking service. This server allows AI models to query and analyze error reports and events on Sentry.
get_sentry_issue
Tool
issue_id_or_url
(string): Sentry issue ID or URL to analyzesentry-issue
Prompt Template
issue_id_or_url
(string): Sentry issue ID or URL# Install dependencies npm install # Build the project npm run build
The server is configured using environment variables. Create a .env
file in the project root directory:
# Required: Sentry authentication token
SENTRY_AUTH_TOKEN=your_sentry_auth_token
# Optional: Sentry organization name
SENTRY_ORGANIZATION_SLUG=your_organization_slug
# Optional: Sentry project name
SENTRY_PROJECT_SLUG=your_project_slug
# Optional: Sentry base url
SENTRY_BASE_URL=https://sentry.com/api/0
Alternatively, you can set these environment variables at runtime.
Run the server via standard IO:
node dist/index.js
Debug with MCP Inspector:
npx @modelcontextprotocol/inspector node dist/index.js
SENTRY_AUTH_TOKEN
(required): Your Sentry API access tokenSENTRY_PROJECT_SLUG
(optional): The slug of your Sentry projectSENTRY_ORGANIZATION_SLUG
(optional): The slug of your Sentry organizationThe latter two variables can be omitted if project and organization information are provided in the URL.
This project is licensed under the MIT License.
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