# Honeybadger — MCP server on mcp.ai
> Connect your Honeybadger account and use 7 tools for server monitoring straight from your AI agent. Connect with your own API key. Honeybadger is an error tracking and application performance monitoring service for developers.

By: mcp.ai · official
Page: https://mcp.ai/honeybadger

## Connect (MCP protocol)
Remote MCP endpoint (HTTP, streamable): https://api.mcp.ai/p_honeybadger?ms=1787291400000
Add it as a custom/remote MCP connector, then authenticate when prompted.

## REST API (no MCP client required)
Every tool is also a REST endpoint, authed with a workspace API key.
Discover: GET https://api.mcp.ai/api/honeybadger/_endpoints   # public; lists every endpoint
Call:     POST https://api.mcp.ai/api/honeybadger/<endpoint>
  Authorization: Bearer sk_live_…   # create one at https://mcp.ai/settings/api-keys
  Content-Type: application/json
  Body: { …args }   →   { "ok": true, "tool": "<id>", "result": { … } }

## Developer docs
How to use (MCP or REST), markdown: https://mcp.ai/honeybadger/skill.md
Postman collection (v2.1): https://mcp.ai/honeybadger/postman.json

## Tools
- honeybadger_report_check_in(id?: string, slug?: string, project_api_key?: string) — Reports a check-in (ping) to Honeybadger for uptime monitoring. Check-ins are used to monitor scheduled tasks, cron jobs, and background processes. By pinging this endpoint regularly, you signal that 
- honeybadger_report_check_in_with_payload(check_in: object, check_in_id: string) — Report a check-in with additional payload data to Honeybadger. Use when monitoring scheduled tasks or cron jobs and need to send metrics, status, or metadata (up to 20KB).
- honeybadger_report_deployment(deploy: object) — Report a new deployment to Honeybadger for deployment tracking and error correlation. Use this tool after deploying code to notify Honeybadger, which allows you to: - Track deployment history on your 
- honeybadger_report_event(events: object[]) — Send custom events to Honeybadger Insights for tracking, monitoring, and analytics. Use this action to record any structured event data such as: - User activity and behavioral events (logins, page vie
- honeybadger_report_exception(error: object, server?: object, request?: object, notifier?: object, breadcrumbs?: object) — Tool to report an exception notice to Honeybadger. Use when sending error details (stack trace, context) for diagnostics.
- honeybadger_upload_file_to_s3(file: object, desired_name?: string) — Tool to upload a local file to a managed S3 bucket. Use when preparing files for source-map uploads.
- honeybadger_upload_source_map(revision?: string, source_map: object, minified_url: string, minified_file: object, additional_source_files?: object[]) — Upload JavaScript source maps to Honeybadger for error stack trace de-minification. Use this tool after deploying minified JavaScript assets to enable Honeybadger to display un-minified, readable stac

## Example prompts
- "What can I do in Honeybadger?"
- "Show me a summary of my Honeybadger account"

## Links
Docs: https://mcp.ai/docs/mcps/honeybadger
Website: https://mcp.ai/mcps/honeybadger