How to Use the DataDome MCP in Pydantic AI

Q: How do I initialize the toolset in my Pydantic AI code?

Import MCPToolset and pass the HTTP endpoint of your managed Vinkius MCP server. Add the toolset to your agent's configuration to expose all ten security tools instantly.

Q: Where are the DataDome access logs stored during validation?

The listaccesslogs tool streams raw log data directly into your local Pydantic AI agent memory. No logs are stored on Vinkius disks, ensuring your user traffic data remains private and ephemeral.

Run type-safe security audits on your DataDome logs with Pydantic AI validation guarding every schema.

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Connect DataDome MCP to Pydantic AI

Create your Vinkius account to connect DataDome 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 DataDome with Pydantic AI

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Type-Safe Bot Traffic Summaries

The `get_bot_traffic_summary` tool returns a structured breakdown of good versus bad bots hitting your system. Pydantic AI validates this payload against strict schemas, ensuring your agent never processes corrupted or malformed traffic data. If the API format changes, your agent raises a validation error immediately instead of hallucinating fake traffic metrics. This guarantees that your security dashboards and automated alerts are built on 100% verified numbers.

Validate Threat Details and Detection Logic

The `get_threat_details` tool extracts deep behavioral patterns, request headers, and specific detection signatures for any threat ID. Your agent parses this complex JSON structure with absolute type safety. Because Pydantic AI enforces type boundaries, your agent can safely extract specific fields like origin IPs or User-Agents. It can then pass these verified strings to your blocking scripts without risking injection attacks or runtime crashes.

Audit Edge Rules with Strict Schemas via MCP Server

The `list_custom_bot_rules` tool exposes your active IP and User-Agent blocklists directly to your validation pipeline. Your agent reads this list to verify that every active rule conforms to your internal security policies. This MCP Server integration allows you to build automated compliance checks. The agent flags any rule that has an invalid priority or missing match criteria, keeping your edge firewall clean and predictable.

Setup guide

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

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

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

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Common questions about DataDome MCP in Pydantic AI

The framework wraps the MCP Server tool outputs in Pydantic models. When your agent calls `get_protection_stats`, the incoming JSON is validated against these models before the agent can read it.

The agent raises a validation error instantly. This prevents your agent from making decisions based on unverified threat categories or corrupted API responses.

Yes, the server is model-agnostic. You can connect it to local models via Ollama or run it with Anthropic and OpenAI while maintaining full type safety.

Import `MCPToolset` and pass the HTTP endpoint of your managed Vinkius MCP server. Add the toolset to your agent's configuration to expose all ten security tools instantly.

The `list_access_logs` tool streams raw log data directly into your local Pydantic AI agent memory. No logs are stored on Vinkius disks, ensuring your user traffic data remains private and ephemeral.

Use it with your favorite AI tools

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