How to Use the 42Crunch MCP in Pydantic AI

Q: Does Pydantic AI validate 42Crunch tool inputs?

Yes, every parameter sent to tools like triggeraudit is validated at runtime. The framework catches malformed IDs or missing arguments before the request ever leaves your machine.

Q: What happens if an API deletion fails?

Calling deleteapi returns a specific status code. If the response violates the expected Pydantic schema, the agent throws a validation error and halts the pipeline immediately.

Enforce strict type safety on 42Crunch security reports using Pydantic AI.

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Connect 42Crunch MCP to Pydantic AI

Create your Vinkius account to connect 42Crunch 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 42Crunch with Pydantic AI

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Type-Safe 42Crunch MCP Server

Calling `get_scan_report` through this framework guarantees the returned vulnerability data matches your exact Pydantic models. If the testing platform returns an unexpected field format, the agent fails loudly instead of silently corrupting your database. This strict validation matters when you automate security workflows. You know exactly what shape the `get_audit_report` data will take, allowing your code to parse CVSS scores and remediation steps with absolute certainty.

Manage Testing Workspaces

The `list_collections` and `list_apis` tools give your agent a structured map of your entire testing inventory. It retrieves unique IDs and security scores as strictly typed lists. Pushing new definitions happens via `import_api`. Once ingested, the agent can call `get_api` to verify the metadata, or clean up obsolete definitions using `delete_api` if the endpoint is deprecated.

Automated Security Audits

Your agent initiates fresh static analysis by executing `trigger_audit` on a specific definition ID. It tracks the progress and handles the asynchronous response perfectly. For live endpoints, `list_scans` pulls the history of dynamic conformance tests. The agent evaluates these historical runs to determine if the API meets your deployment criteria.

Setup guide

Set up 42Crunch 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": {
        "42crunch-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to 42Crunch tools.",
)

result = await agent.run("List recent 42Crunch transactions")
print(result.output)

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Common questions about 42Crunch MCP in Pydantic AI

Install the slim package using pip install "pydantic-ai-slim[mcp]". Initialize the connection using MCPToolset("http://...") and pass it into your Agent via the toolsets parameter.

Yes, every parameter sent to tools like trigger_audit is validated at runtime. The framework catches malformed IDs or missing arguments before the request ever leaves your machine.

Correctness over speed. When dealing with security scores and vulnerability data, you need absolute certainty that the agent parsed the JSON correctly without hallucinating missing fields.

Calling delete_api returns a specific status code. If the response violates the expected Pydantic schema, the agent throws a validation error and halts the pipeline immediately.

Vinkius manages the authentication layer using a single endpoint token while isolating the runtime. Your API security scores and static audit reports flow through a zero-trust sandbox that retains absolutely nothing.

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