Hunter MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create New Lead, Enrich Email Data, Find Person Email, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Hunter through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Hunter app connector for Pydantic AI is a standout in the Sales Automation category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Hunter "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Hunter?"
)
print(result.data)
asyncio.run(main())
* 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 Hunter MCP Server
Connect your Hunter account to any AI agent and power your email prospecting through natural conversation.
Pydantic AI validates every Hunter tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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
- Domain Search — Find all professional email addresses associated with a domain or company name
- Email Finder — Discover the most likely email address for a specific person by name and company
- Email Verification — Check the validity and deliverability of any email address with confidence scores
- Email Count — Check how many email addresses are available for a domain before searching
- Contact Enrichment — Retrieve all available professional data (title, company, social profiles) for an email address
- Lead Management — Create, list, update, and delete leads in your Hunter CRM with lead list organization
- Account Monitoring — Track remaining API credits and account usage
The Hunter MCP Server exposes 12 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.
All 12 Hunter tools available for Pydantic AI
When Pydantic AI connects to Hunter through Vinkius, your AI agent gets direct access to every tool listed below — spanning email-finder, domain-search, email-verification, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Save lead to CRM
Get contact intel
Find personal email
Check credits
Check email availability
Get lead info
List lead lists
List lead profiles
Delete lead record
Find emails for domain
Modify lead data
Check deliverability
Connect Hunter to Pydantic AI via MCP
Follow these steps to wire Hunter into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Hunter MCP Server
Pydantic AI provides unique advantages when paired with Hunter 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 Hunter integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Hunter connection logic from agent behavior for testable, maintainable code
Hunter + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Hunter MCP Server delivers measurable value.
Type-safe data pipelines: query Hunter with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Hunter tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Hunter and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Hunter responses and write comprehensive agent tests
Example Prompts for Hunter in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Hunter immediately.
"Find all emails at stripe.com and verify the CTO's email address."
"Find the email for Sarah Chen at Acme Corp and enrich her contact data."
"Check my Hunter account credits and list all saved leads."
Troubleshooting Hunter MCP Server with Pydantic AI
Common issues when connecting Hunter to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiHunter + Pydantic AI FAQ
Common questions about integrating Hunter MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.