StackHawk MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect StackHawk through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 StackHawk "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in StackHawk?"
)
print(result.data)
asyncio.run(main())
* 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 StackHawk MCP Server
Integrate the robust dynamic application security testing (DAST) capabilities of StackHawk directly into your conversational AI. Empower your engineering team to monitor system vulnerabilities, initiate complex scans, and orchestrate proactive security protocols without relying heavily on static dashboards. Connect securely to your workspaces, instruct your AI to assess ongoing security threats, and automatically classify alerts through a natural language interface designed to accelerate risk remediation across modern CI/CD pipelines.
Pydantic AI validates every StackHawk 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
- Automated Scanning — Programmatically initiate comprehensive security evaluations across your environments utilizing
run_scan, and halt operations securely targeting specific execution UUIDs viastop_scan. - Risk Assessment — Effectively audit environments by listing operational scans with
list_scans, or retrieve deep vulnerability reports invokingget_alertstargeting specific scan iterations. - Application Management — Catalog active software deployments monitored by StackHawk utilizing
list_applications, and manage organizational parameters inspecting environments directly vialist_environments. - Triage & Operations — Authenticate securely establishing a valid operational bearer token with
login, and instruct the AI to accurately qualify, dismiss, or assign statuses prioritizing critical mitigation efforts usingtriage_alert.
The StackHawk 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 StackHawk to Pydantic AI via MCP
Follow these steps to integrate the StackHawk 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 StackHawk with type-safe schemas
Why Use Pydantic AI with the StackHawk MCP Server
Pydantic AI provides unique advantages when paired with StackHawk 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 StackHawk integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your StackHawk connection logic from agent behavior for testable, maintainable code
StackHawk + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the StackHawk MCP Server delivers measurable value.
Type-safe data pipelines: query StackHawk with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple StackHawk tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query StackHawk and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock StackHawk responses and write comprehensive agent tests
StackHawk MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect StackHawk to Pydantic AI via MCP:
get_application_details
Get detailed configuration for a specific StackHawk application
get_organization_details
Get StackHawk organization details and subscription tier
get_scan_alerts
Download individual security alerts discovered by a DAST scan
get_scan_results
Get detailed results and metadata for a specific DAST scan
list_api_keys
Useful for auditing and hygiene. List API keys configured for a StackHawk organization
list_applications
Requires a Bearer token and organization ID. List all registered DAST applications in a StackHawk organization
list_environments
g., Development, Staging, Production) configured on the application. List configured scan environments for a StackHawk application
list_scans
Includes scan IDs and high-level alert counts. List all DAST scan executions for a StackHawk application
login
This token is required for all subsequent StackHawk tool calls. Authenticate and obtain a Bearer access token from StackHawk
triage_alert
Valid statuses: RISK_ACCEPTED, FALSE_POSITIVE, IN_PROGRESS. Triage a DAST security alert (accept risk, false positive, etc.)
Example Prompts for StackHawk in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with StackHawk immediately.
"Log in with my API token, list my projects and environments, then show the critical vulnerabilities from the latest scan."
"Run a new scan against the Production application."
Troubleshooting StackHawk MCP Server with Pydantic AI
Common issues when connecting StackHawk to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiStackHawk + Pydantic AI FAQ
Common questions about integrating StackHawk MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect StackHawk with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect StackHawk to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.