BugSnag MCP. Monitor system stability with conversation.
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BugSnag lets your AI agent monitor application stability and track live production errors. Querying BugSnag means you can ask questions about system health—like 'What's wrong with the Android app?' or 'Show me the top three error types this week.' You get instant access to error groups, event details, and project-wide statistics without opening a dashboard.
What your AI agents can do
Get error
Retrieves comprehensive details for one selected error group.
Get event
Pulls full details for one specific, unique error event ID.
Get project
Gets detailed information about a single, specified project.
Discover every organization or project within BugSnag to scope out the area needing monitoring.
Pull aggregated error statistics to understand how application performance changes over time for a given project.
View every distinct group of errors tied to a specific project, including their severity and frequency counts.
Pull deep metadata for one specific error group, detailing its class and how often it's showing up.
Retrieve lists of discrete error events, allowing you to pinpoint the exact time and context of a bug occurrence.
List release stages and collaborators to ensure everyone working on the code is aligned with the current production status.
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Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
BugSnag: 10 Tools for Error Management
These ten tools allow your agent to find project information, list all errors and events, track trends, and get deep metadata on any failure point.
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Start using BugSnag on Vinkius019d7565get error
Retrieves comprehensive details for one selected error group.
019d7565get event
Pulls full details for one specific, unique error event ID.
019d7565get project
Gets detailed information about a single, specified project.
019d7565get project stats
Provides statistical reports and trends on the overall error performance of a project over time.
019d7565list collaborators
Lists the users and roles who work within a specific organization.
019d7565list errors
Gathers a list of error groups associated with a specific project.
019d7565list events
Gathers a list of individual failure events that occurred within a project timeframe.
019d7565list organizations
Lists every BugSnag organization account you have access to.
019d7565list projects
Retrieves all projects housed within a selected organization.
019d7565list release stages
Shows all deployment stages configured for a given project (e.g., staging, production).
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Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The Dashboard Rabbit Hole
Right now, finding out why your app broke is a manual process of clicking tabs: You jump into the monitoring dashboard. Then you select the right project from the dropdown. Next, you filter by severity and date range. If that doesn't work, you copy an error code and paste it into another tool to see if collaborators have already found it. It’s tedious, repetitive clicking.
With this MCP, all that friction disappears. You simply tell your agent, 'Check the stability of Project X for errors that happened last week.' The agent handles the project selection, the filtering by date, and the grouping of results. You just get the answer.
BugSnag: Getting Contextual Error Reports
You don't have to manually switch between 'Error Groups' views and 'Event Details' views anymore. Your agent handles that transition for you, first showing the error class (via `list_errors`), and then using that information to run `get_event` on a specific ID to pull all the surrounding metadata.
The difference is control. You guide the investigation without ever leaving your chat window or needing to copy-paste IDs between different monitoring tabs.
What you can do with this MCP connector
When your application fails, finding out why used to mean clicking through multiple dashboards, filtering by date range, and cross-referencing error codes. This MCP lets you do all that—via natural conversation.
You can ask for high-level visibility across your entire tech stack, listing every organization or project you manage. Need to know the current state of a specific release? You can check deployment stages and see which collaborators are involved. If you spot an error group, you don't stop there; you drill down instantly, pulling individual event details for debugging.
This capability is critical because it allows your agent to chain together context: first identifying a project with issues, then listing the specific error groups, and finally retrieving detailed metadata for that exact failure event. Because this MCP runs on Vinkius, every tool call generates a cryptographically signed audit trail, giving you a tamper-proof history of exactly what data flowed through and how your agent used it.
019d7565-6ab9-73c4-987b-f054f3d60a55 
How BugSnag MCP Works
- 1 Subscribe to this MCP and provide your BugSnag Personal Auth Token.
- 2 Connect your AI client, like Cursor or Claude, and prompt it to check system health for a specific project.
- 3 The agent uses the available tools to gather error groups, trends, and event details, delivering a cohesive status report.
The bottom line is you get immediate, contextualized data about your application's stability, without having to navigate multiple dashboards yourself.
Who Is BugSnag MCP For?
Software Engineers and SREs. This MCP helps the engineer who's tired of clicking through complex dashboard menus at 2 am. It lets them query error data directly into their workflow, saving minutes that stack up to hours.
Monitoring stability trends and checking the health of specific release stages before a major deployment.
Debugging an immediate failure by getting detailed metadata for a specific error event or group ID.
Getting high-level, quantitative statistics on error frequency across different projects to prioritize bug fixes against business impact.
What Changes When You Connect
- Go from 'What's wrong?' to 'Here are the 5 latest errors.' Instead of clicking through pages in a dashboard, you ask your agent and get immediate structured data on event details or error groups.
- Pinpoint trends using
get_project_stats. You don't just see an error happened; you see if that particular error class is getting worse over the last 30 days. This helps prove bug prioritization to PMs. - Get full context with project scoping tools like
list_organizationsandlist_projects. You can ask your agent to limit its search only to projects within a specific business unit, narrowing down the noise fast. - Understand who's on the team using
list_collaboratorsand which deployment stage is active vialist_release_stages. This gives you immediate context when investigating why an error only appears in 'Staging'. - Access granular failure data with
get_event. Instead of viewing a summary, you pull the raw metadata for one specific bug instance, crucial for reproducing and fixing the issue. - Contextualize your investigation by pairing tools. Use
list_projectsto find all targets, then use that output list when callinglist_errorsto get grouped data.
Real-World Use Cases
Debugging a sudden spike in errors.
An engineer sees an alert for 'Auth Failure' and needs details. They prompt the agent to run get_error using the error group ID, immediately showing the failure class, severity, and rate of occurrence without leaving their terminal.
Preparing a weekly stability report.
A Product Manager asks for 'Project X's performance trends.' The agent runs get_project_stats, compiling error rates and counts across the last quarter, which the PM can then use in a meeting deck.
Verifying team access before launch.
An SRE needs to confirm who has permission to deploy. They run list_collaborators for the target organization and cross-reference that list with the required roles listed in list_release_stages.
Troubleshooting a deployment environment.
A developer suspects the error only happens on one build. They ask the agent to check the status using get_project and cross-reference that with list_release_stages to confirm if 'Beta' or 'Production' is currently active.
The Tradeoffs
Asking for a general bug list.
Prompting the agent: 'Show me all bugs.' The response will be vague, giving too much noise and no actionable context because it doesn't know which project or time window you mean.
→
Always narrow the scope. First, use list_projects to name the target area. Then, ask the agent to run list_errors against that specific project ID for focused results.
Confusing error groups with events.
Asking 'What happened yesterday?' The agent can't answer because you need both a time range and an action. It will give a generic list of failures, which is usually useless for root cause analysis.
→
Use list_events to get the timeline (the 'what' and 'when'). Then use get_event on a specific ID to find the detailed metadata (the 'why').
Over-relying on one tool.
Running only list_projects and stopping. You know what projects exist, but you don't know if they are actively failing or stable in production.
→
Always pair discovery with monitoring. After running list_projects, immediately follow up by asking the agent to run get_project_stats for those returned IDs.
When It Fits, When It Doesn't
Use this MCP if your primary job involves diagnosing, tracking, or reporting on application failure rates and stability. This is essential when you need to correlate error groups with project scope or deployment status. You absolutely must use it when an issue requires historical context; for example, checking get_project_stats tells you if the problem is a sudden spike (an event) or a slow creep over time (a trend).
Don't use this MCP if your goal is general resource management. If you need to manage user accounts, read billing records, or update product documentation, BugSnag isn't the tool. Those tasks require a dedicated CRM or Wiki-type MCP. Only bring in an agent when the data point you need relates directly to code execution and system health.
Common Questions About BugSnag MCP
How do I find out what errors are spiking for my app using get_project_stats? +
Run get_project_stats and specify the time frame you're interested in. This tool compiles error trends over time, showing if a single failure point is becoming significantly worse or better.
What do I need to know before using list_events? +
You only need to tell the agent which project you're investigating. list_events then gives you a clean, chronological list of unique failure occurrences that happened in that scope.
Can I find out what version is running when getting_project? +
While get_project gives overall project details, use list_release_stages first. This tool shows the available deployment stages (like 'Staging' or 'Production'), which helps narrow down your context.
What is the difference between list_errors and get_error? +
list_errors gives you a high-level overview—a directory of every distinct error type. get_error takes one ID from that list and provides all the deep, specific metadata about just that single error group.
What information does `list_organizations` return, and how do I select my active scope? +
It returns a list of all organizations you have access to. You must use the returned organization ID in subsequent calls to ensure your agent is querying data from the correct scope.
Before debugging an error group, how do I check the team structure using `list_collaborators`? +
This tool lists all collaborators within an organization. This helps you confirm which roles or teams need to investigate a specific issue before running detailed calls like get_error.
When calling `list_release_stages`, what does the output tell me about deployment context? +
It shows all configured release environments, such as 'Staging' or 'Production'. This context is vital because you should use this information when querying error tools to know exactly which environment reported the failure.
What specific metadata do I get when running `get_event`? +
You receive the full stack trace, exact occurrence details, and timestamps. This comprehensive data lets your agent pinpoint the failing function or line number, speeding up debugging immensely.
Multi-server workflows that include BugSnag MCP
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