How to Use the Beagle Security MCP in Pydantic AI

Validate all Beagle Security test results with type-safe Pydantic AI models.

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Connect Beagle Security MCP to Pydantic AI

Create your Vinkius account to connect Beagle Security 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 Beagle Security with Pydantic AI

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Type-safe security scans for Pydantic AI

Your agent requests scan details using `get_test_result`. Because you use Pydantic AI, the incoming JSON is validated against your models, catching any API changes instantly. If the server returns malformed data, your agent raises a validation error instead of crashing. This guarantees your security reports are always structured correctly for your downstream logic.

Manage test lifecycles in Pydantic AI

Launch new security checks with `start_test` directly from your agent's control loop. The tool returns a confirmation that your Pydantic model parses without extra effort. You can keep track of ongoing work by using `get_running_tests`. It provides a current snapshot of your security pipeline so your agent knows exactly when to wait or proceed.

Query project data via Pydantic AI tools

Use `list_projects` to define the scope of your security automated checks. Your agent iterates through these project IDs to perform targeted scans on specific applications. Call `get_application` to pull granular details for each target. This gives your agent the necessary metadata to format professional vulnerability reports automatically.

Setup guide

Set up Beagle Security 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": {
        "beagle-security-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Beagle Security MCP in Pydantic AI

Every tool call is checked against your Pydantic models at runtime. If the server returns unexpected fields, the agent stops immediately to prevent silent data corruption.

Yes, this MCP Server is model-agnostic. Whether you use local LLMs or cloud providers, the toolset remains fully compatible with your Pydantic AI setup.

Install the slim MCP package, define your MCPToolset with the server URL, and add it to your Agent's toolsets list. The server must be running externally.

The server exposes nine tools. You can view them by checking your agent's tool registry after the MCPToolset initializes.

The server only handles your test session metadata and vulnerability findings. Vinkius ensures your data remains protected during the HTTP exchange.

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