Can I check the stability trend for a project using the agent?

Yes! Use the `get_project_stats` tool with the Project ID. Your agent will fetch the error trends and statistics, allowing you to monitor health over time.

How do I list the top errors for my application?

Simply ask the agent to `list_errors` and provide the Project ID. It will retrieve the error groups from your BugSnag account, including messages and event counts.

Does the integration allow inspecting a specific error occurrence?

Yes. Use the `get_event` tool with the Event ID. It will retrieve the full details for that specific occurrence, which is helpful for deep debugging.

BugSnag MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: BugSnag
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect BugSnag through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to BugSnag "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in BugSnag?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About BugSnag MCP Server

Connect your BugSnag account to any AI agent and orchestrate your error monitoring, stability tracking, and incident response workflows through natural conversation.

Pydantic AI validates every BugSnag tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Organization Oversight — List all your organizations and projects to maintain visibility across your entire tech stack.
Error Management — List and inspect error groups for specific projects, including error classes, severity, and frequency.
Event Deep Dives — Retrieve individual error events and occurrence details to debug issues faster.
Team Coordination — Access your directory of collaborators and release stages to ensure everyone is aligned.
Stability Insights — Retrieve error trends and statistics to monitor the health of your applications over time.
Incident Response — Get detailed metadata for specific error or event IDs straight from your workspace.

The BugSnag MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect BugSnag to Pydantic AI via MCP

Follow these steps to integrate the BugSnag MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from BugSnag with type-safe schemas

Why Use Pydantic AI with the BugSnag MCP Server

Pydantic AI provides unique advantages when paired with BugSnag through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your BugSnag integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your BugSnag connection logic from agent behavior for testable, maintainable code

BugSnag + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the BugSnag MCP Server delivers measurable value.

Type-safe data pipelines: query BugSnag with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple BugSnag tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query BugSnag and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock BugSnag responses and write comprehensive agent tests

BugSnag MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect BugSnag to Pydantic AI via MCP:

get_error

Get details of a specific error group

get_event

Get details of a specific error event

get_project

Get details of a specific project

get_project_stats

Get error trends and statistics for a project

list_collaborators

List collaborators in an organization

list_errors

List error groups for a project

list_events

List individual error events for a project

list_organizations

List all organizations you have access to

list_projects

List all projects in an organization

list_release_stages

List release stages configured for a project

Example Prompts for BugSnag in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with BugSnag immediately.

"List all my projects in BugSnag for organization org_123."

"Show the last 5 errors for the 'Web Dashboard' project."

"Get details for error group err_99283."

Troubleshooting BugSnag MCP Server with Pydantic AI

Common issues when connecting BugSnag to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

BugSnag + Pydantic AI FAQ

Common questions about integrating BugSnag MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your BugSnag MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.