How do I get a Datanyze API Token?

Log in to your Datanyze account, navigate to the API section in your settings, and you can retrieve your unique API Token from there.

What are technographics?

Technographics refers to the analysis of the software and technology tools a company uses, such as their CRM, cloud provider, or analytics platform.

Does searching for a domain use credits?

Yes, most Datanyze API calls consume credits based on your current plan. You can use the get_api_credit_balance tool to monitor your remaining credits.

Datanyze MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Datanyze
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Datanyze through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Datanyze "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Datanyze?"
    )
    print(result.data)

asyncio.run(main())

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* 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 Datanyze MCP Server

Integrate Datanyze, the leader in technographics and B2B intelligence, directly into your AI workflow. Research target companies, identify the software technologies they use, and retrieve contact information for key decision-makers using natural language.

Pydantic AI validates every Datanyze 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

Technographic Auditing — Identify the CMS, CRM, marketing automation, and other technologies used by any domain.
Lead Generation — Search for B2B companies by industry or keyword and retrieve contact profiles.
Market Analysis — Find domains similar to your competitors and track global traffic ranks.
Credit Monitoring — Keep track of your Datanyze API credit balance directly via chat.

The Datanyze 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 Datanyze to Pydantic AI via MCP

Follow these steps to integrate the Datanyze 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 Datanyze with type-safe schemas

Why Use Pydantic AI with the Datanyze MCP Server

Pydantic AI provides unique advantages when paired with Datanyze 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 Datanyze integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Datanyze connection logic from agent behavior for testable, maintainable code

Datanyze + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Datanyze MCP Server delivers measurable value.

Type-safe data pipelines: query Datanyze with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Datanyze tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Datanyze and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Datanyze responses and write comprehensive agent tests

Datanyze MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Datanyze to Pydantic AI via MCP:

get_api_credit_balance

Check your remaining Datanyze API credits

get_domain_contacts

Resolves individual profiles including job titles, departments, and professional social links for identified decision-makers. List key decision-makers and contact profiles for a domain

get_domain_intelligence

Returns a comprehensive profile including active software stacks, website metadata, and organizational technographic attributes. Retrieve technographics and metadata for a specific domain

get_domain_traffic_rank

Retrieve the global traffic rank for a specific domain

list_competitor_domains

Returns a list of domains sharing similar technographic profiles or industry characteristics. Find domains similar to or competing with a specific domain

list_industry_sectors

List all industry categories available for filtering

list_technology_customers

Returns a list of company domains currently identified as users of the specified platform. List companies currently using a specific technology ID

list_tracked_technologies

Returns a list of technical identifiers and category classifications for various software solutions. List all software technologies and platforms tracked by Datanyze

quick_tech_audit

Identify core technologies used by a domain

search_b2b_companies

Matches query terms against company names, industry sectors, and descriptive metadata to return a list of matching organizational entities. Search for companies matching a specific keyword or industry

Example Prompts for Datanyze in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Datanyze immediately.

"What technologies are used by 'stripe.com'?"

"Find B2B companies in the 'Fintech' industry in London."

"How many API credits do I have left?"

Troubleshooting Datanyze MCP Server with Pydantic AI

Common issues when connecting Datanyze to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Datanyze + Pydantic AI FAQ

Common questions about integrating Datanyze MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Datanyze MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.