How to Use the BugSnag MCP in Pydantic AI

Q: Can Pydantic AI list BugSnag collaborators?

Yes, use listcollaborators. The response is mapped to your Pydantic model, making it easy to identify the right person to ping for a fix.

Q: How do I query error groups in Pydantic AI?

Use listerrors with your project ID. Your agent will receive a validated list of error groups, ready for immediate processing.

Validate and track BugSnag errors with Pydantic AI type-safety.

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Connect BugSnag MCP to Pydantic AI

Create your Vinkius account to connect BugSnag to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup BugSnag with Pydantic AI

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Type-safe error inspection with Pydantic AI

Ensure every error detail you pull with `get_event` matches your expected schema. Pydantic AI forces the data into a rigid structure, preventing your agent from hallucinating fields. If the data doesn't fit, the agent stops immediately. It keeps your debugging logic reliable and predictable.

Monitor release health in Pydantic AI

Use `list_release_stages` to keep your agent informed of your environment topology. Every response is validated against the model you define in your agent. This keeps your agent aware of where it's looking. It prevents the common mistakes that happen when you guess environment names.

Fetch project metadata using Pydantic AI

Call `list_projects` to refresh your agent's knowledge of your organization. It ensures your agent is always talking about the right service. Since everything is validated at runtime, you don't have to worry about silent failures. You get clean, typed data every single time.

Setup guide

Set up BugSnag MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "bugsnag-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to BugSnag tools.",
)

result = await agent.run("List recent BugSnag transactions")
print(result.output)

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Common questions about BugSnag MCP in Pydantic AI

The MCP Server returns JSON that your agent automatically validates. If the structure is off, Pydantic AI throws a validation error before the agent attempts to use the data.

Yes, use `list_collaborators`. The response is mapped to your Pydantic model, making it easy to identify the right person to ping for a fix.

The server uses ephemeral connections that terminate once the task is complete. No BugSnag error information is persisted on our side, keeping your Pydantic AI workflow isolated and private.

Use `list_errors` with your project ID. Your agent will receive a validated list of error groups, ready for immediate processing.

Yes, all 10 tools are exposed as typed functions. Your Pydantic AI agent can call them as long as your configuration provides the necessary endpoint token.

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