Can I check the scope of a security program using the agent?

Yes! Use the `get_program` tool with the Program ID. Your agent will fetch the detailed metadata, including targets and scope descriptions, from Bugcrowd.

How do I list all the vulnerability submissions for my account?

Simply ask the agent to `list_submissions`. It will retrieve the latest vulnerability reports from your Bugcrowd account, including titles and statuses like 'triaged' or 'resolved'.

Does the integration allow creating a new submission?

Yes. Use the `create_submission` action and provide the title and description. You can also associate it with a specific program by providing the `program_id`.

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

Name: Bugcrowd
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 Bugcrowd through 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 Bugcrowd "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Bugcrowd?"
    )
    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 Bugcrowd MCP Server

Connect your Bugcrowd account to any AI agent and orchestrate your vulnerability management, bug bounty programs, and security engagements through natural conversation.

Pydantic AI validates every Bugcrowd tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through 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

Submission Oversight — List and retrieve detailed metadata for all vulnerability reports (submissions) across your programs.
Program Management — List all active security programs and retrieve detailed metadata, including scopes and rewards.
Engagement Tracking — Monitor crowd executions like specific Bug Bounties or Pen Tests directly from your workspace.
Target Coordination — List and inspect assets in scope (targets) for your organization or specific programs.
Submission Creation — Create new vulnerability submissions from external sources using natural language.
Organizational Insights — Retrieve core organization information and settings straight from your workspace.

The Bugcrowd 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 Bugcrowd to Pydantic AI via MCP

Follow these steps to integrate the Bugcrowd 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 Bugcrowd with type-safe schemas

Why Use Pydantic AI with the Bugcrowd MCP Server

Pydantic AI provides unique advantages when paired with Bugcrowd 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 Bugcrowd integration code

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

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

Bugcrowd + Pydantic AI Use Cases

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

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

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

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

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

Bugcrowd MCP Tools for Pydantic AI (10)

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

create_submission

Create a new vulnerability submission

get_engagement

Get details of a specific engagement

get_organization_info

Retrieve core organization information

get_program

Get details of a specific security program

get_submission

Get details of a specific submission

get_target

Get details of a specific target

list_engagements

List all crowd engagements (bounties, pen tests)

list_programs

List all security programs

list_submissions

List all vulnerability submissions

list_targets

List all assets in scope (targets)

Example Prompts for Bugcrowd in Pydantic AI

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

"List all active security programs in Bugcrowd."

"Show the last 5 vulnerability submissions."

"Create a new submission titled 'Insecure Direct Object Reference' for program prog_123."

Troubleshooting Bugcrowd MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Bugcrowd + Pydantic AI FAQ

Common questions about integrating Bugcrowd 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 Bugcrowd MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.