urlDNA MCP Server

Blog

The urlDNA MCP Server enables native tool use for security-focused LLM agents like OpenAI GPT, Google Gemini and Claude Desktop, providing a direct interface to interact with the urlDNA threat intelligence platform via API.

The repository exposes the same toolset over two transports:

• stdio for local desktop integrations such as Claude Desktop.
• streamable-http for hosted deployments such as Cloud Run.

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Installation & Setup

This project uses uv for fast Python package management.

Prerequisites

Install uv if you haven't already:

# On macOS and Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

# Or with pip
pip install uv

Quick Start

1. Clone and setup the project:

git clone <repository-url>
cd urlDNA-mcp-server
uv sync

2. Run the MCP server locally (stdio mode):

uv run python urldna_mcp/run.py

3. Run the MCP server in streamable HTTP mode:

uv run python urldna_mcp/server.py

The hosted server reads these environment variables:

• PORT: HTTP port to bind to. Defaults to 8080.
• MCP_PATH: Public MCP endpoint path. Defaults to /.

Development

# Install development dependencies
uv sync --dev

# Run tests (when available)
uv run pytest

# Format code
uv run black .

# Type checking
uv run mypy .

# Lint code
uv run flake8 .

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Hosted MCP Server

The urlDNA MCP server is already hosted and available at:

https://mcp.urldna.io/

This server is accessible over streamable HTTP, which makes it suitable for Cloud Run and other request-driven platforms.

You can use it directly with any platform or LLM that supports the MCP specification (e.g., Claude Desktop, OpenAI GPT, Google Gemini).

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Supported Tools

Scanning

Tool	Description
fast_check	Instantly check if a URL has been scanned. Returns SAFE / MALICIOUS / UNRATED.
new_scan	Submit a URL for a full scan and wait for the result (~30–60s).
get_scan	Retrieve a complete scan result by ID.

Search

Tool	Description
search	Search scans using CQL (Custom Query Language) across domain, IP, technology, malicious flag, and more. Supports AND and OR expressions plus pagination (page 2+ requires PREMIUM).

Saved Queries

Tool	Description
list_queries	List all saved queries for the authenticated user.
get_query	Retrieve a specific saved query and its filters by ID.
create_query	Create a new saved query with one or more CQL filter conditions.
update_query	Update an existing query's name and filters (full replacement).
delete_query	Permanently delete a saved query by ID.
query_scans	Retrieve all matching scans for a saved query.

Brand Monitoring

Tool	Description
list_brands	List available brands with optional name search and visibility filter (ALL / FREE / PREMIUM / USER_BRANDS).
get_brand	Retrieve full details of a specific brand by ID.
brand_scans	Get all scans associated with a brand. Supports additional CQL filtering.

API Reference

Tool	Description
search_docs	Fetch the full urlDNA OpenAPI and documentations.

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Integration with Claude Desktop

To integrate the urlDNA MCP server in Claude Desktop, update your claude_desktop_config.json:

{
  "mcpServers": {
    "urlDNA": {
      "command": "uv",
      "args": [
        "--directory",
        "<YOUR_PATH>\\urldna_mcp",
        "run",
        "urldna_mcp\\run.py"
      ],
      "env": {
        "x-api-key": "<urlDNA_API_KEY>"
      }
    }
  }
}

Replace <YOUR_PATH> with the parent directory that contains this repository and <urlDNA_API_KEY> with your API key from https://urldna.io.

For hosted MCP clients, point them at https://mcp.urldna.io/ or your own deployed MCP_PATH.

Once configured, you can prompt Claude with natural language, for example:

"Search in urlDNA for malicious scans with title like paypal"

"Create a saved query for mobile scans from Italy that are flagged as malicious"

"Show me all scans associated with the Google brand"

Claude will automatically call the correct tool and return results from the urlDNA platform.

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Using the MCP Server with OpenAI GPT

from openai import OpenAI

# Initialize OpenAI client (assumes OPENAI_API_KEY is set via environment variable)
client = OpenAI()

response = client.responses.create(
    model="gpt-3.5-turbo",  # Note: MCP tool use requires a Responses API-compatible model
    input=[
        {
            "role": "system",
            "content": [{"type": "input_text", "text": "You are a cybersecurity analyst using urlDNA."}]
        },
        {
            "role": "user",
          "content": [{"type": "input_text", "text": "Search in urlDNA for malicious scans with title like paypal or login"}]
        }
    ],
    text={"format": {"type": "text"}},
    reasoning={},
    tools=[
        {
            "type": "mcp",
            "server_label": "urlDNA",
            "server_url": "https://mcp.urldna.io/",
            "headers": {
                "x-api-key": "<URLDNA_API_KEY>"  # Replace with your urlDNA API key
            },
            "allowed_tools": [
                # --- Scanning ---
                "new_scan",       # Submit a URL for a full scan and wait for the result
                "get_scan",       # Retrieve a scan result by ID
                "fast_check",     # Lightweight instant safety check (SAFE / MALICIOUS / UNRATED)

                # --- Search ---
                "search",         # Search scans using CQL (Custom Query Language, AND/OR supported)

                # --- Saved Queries (PREMIUM) ---
                "list_queries",
                "get_query",
                "create_query",
                "update_query",
                "delete_query",
                "query_scans",

                # --- Brand Monitoring (PREMIUM) ---
                "list_brands",
                "get_brand",
                "brand_scans",

                # --- API Reference ---
                "search_docs",
            ],
            "require_approval": "never"
        }
    ],
    temperature=0.7,
    top_p=1,
    max_output_tokens=2048,
    store=True
)

print(response.output)

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Using the MCP Server with Google Gemini

Gemini connects to the urlDNA MCP server via fastmcp, and tools are auto-discovered rather than passed as an allowed_tools list.

import os
import asyncio
from fastmcp import Client
from fastmcp.client.transports import StreamableHttpTransport
from google import genai

async def main():
    # 1. Connect FastMCP client directly to streamable-http
    transport = StreamableHttpTransport(
        "https://mcp.urldna.io/",
        headers={"x-api-key": os.getenv("URLDNA_API_KEY", "YOUR_KEY")},
    )
    client_mcp = Client(transport)

    async with client_mcp:
        ai = genai.Client(vertexai=True, project=os.getenv("GOOGLE_CLOUD_PROJECT", "YOUR_PROJECT_ID"))
        response = await ai.aio.models.generate_content(
            model="gemini-2.5-flash",
            contents="Search in urlDNA for malicious scans with title like paypal",
            # Pass the live MCP session (not just tool declarations) so Gemini
            # can automatically call tools and receive their results.
            config=genai.types.GenerateContentConfig(tools=[client_mcp.session]),
        )

        print(response.text)


if __name__ == "__main__":
    asyncio.run(main())

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Container Deployment

Build and run with Docker:

# Build the container
docker build -t urldna-mcp-server .

# Run the server
docker run -p 8080:8080 -e x-api-key=<URLDNA_API_KEY> urldna-mcp-server

# Optional: override the public MCP path if you do not want /
docker run -p 8080:8080 -e MCP_PATH=/custom-path -e x-api-key=<URLDNA_API_KEY> urldna-mcp-server

# Cloud Run example
gcloud run deploy urldna-mcp-server \
  --source . \
  --allow-unauthenticated \
  --set-env-vars MCP_PATH=/

Search Syntax

The search and brand_scans tools forward the provided CQL directly to the urlDNA API. You can combine conditions with either AND or OR.

Examples:

malicious = true AND technology LIKE wordpress
domain = google.com OR domain = youtube.com
(domain = paypal.com OR title LIKE paypal) AND country_code = IT

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Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Install development dependencies: uv sync --dev
4. Make your changes and ensure tests pass
5. Format code: uv run black .
6. Submit a pull request

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Contact & Support

For support or API access, visit https://urldna.io or email urldna@urldna.io.