How to Use the Bugcrowd MCP in Pydantic AI

Run type-safe Bugcrowd security workflows with Pydantic AI, validating every vulnerability submission at runtime.

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Connect Bugcrowd MCP to Pydantic AI

Create your Vinkius account to connect Bugcrowd 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 Bugcrowd with Pydantic AI

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Type-Safe Vulnerability Triaging in Pydantic AI

Stop worrying about your agent hallucinating submission fields when calling `get_submission` to pull Bugcrowd data. Pydantic AI validates the raw Bugcrowd API response against strict Python type schemas before your code ever runs. If Bugcrowd updates its API payload or returns unexpected null values, the agent fails loudly and immediately. This prevents corrupted data from slipping into your internal ticketing systems or messing up your security metrics.

Strict Target and Scope Validation

Validate active testing scopes with absolute precision by pulling targets using `list_targets`. Using this MCP Server ensures that every asset IP, domain, and severity tier matches your strict internal definitions. The agent maps the returned assets directly to your internal Pydantic models for instant verification. You can confidently automate out-of-scope rejections, knowing the agent cannot hallucinate target boundaries.

Creating Submissions Without Silent Failures

When your automated scanner detects a bug, your agent can log it using `create_submission`. The framework ensures the payload matches the exact schema required by Bugcrowd before the request is even transmitted. By running this MCP Server, your agent validates inputs locally to prevent malformed requests from hitting the API. You save API quota, avoid partial writes, and ensure that every logged vulnerability contains all necessary technical details.

Setup guide

Set up Bugcrowd 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": {
        "bugcrowd-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Bugcrowd MCP in Pydantic AI

Use the MCPToolset class pointing to your Vinkius HTTP URL. Pass this toolset directly into the toolsets list when defining your Pydantic AI agent.

The framework will raise a validation error instantly. This prevents the agent from processing bad data, ensuring your security pipelines remain completely reliable.

Yes. You can connect to your hosted MCP Server on Vinkius using either SSE or Streamable HTTP transports, giving you flexibility in how you deploy your security agent.

Yes, you can define a strict Pydantic schema for your input data, forcing the agent to validate the vulnerability details locally before invoking create_submission.

This MCP Server processes your sensitive program data—including target scopes and vulnerability descriptions—entirely within your local, typed runtime. Vinkius hosts the server in an isolated sandbox, meaning your private security configurations are never stored or logged on our infrastructure.

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