Leadfeeder MCP Server for Pydantic AI 9 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Leadfeeder through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Leadfeeder "
"(9 tools)."
),
)
result = await agent.run(
"What tools are available in Leadfeeder?"
)
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 Leadfeeder MCP Server
Connect your Leadfeeder tracking system to an AI agent to analyze high-quality B2B internet traffic. Track precise analytics without using heavy third-party dashboard setups directly in Cursor or Claude.
Pydantic AI validates every Leadfeeder tool response against typed schemas, catching data inconsistencies at build time. Connect 9 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
- Discover Target Leads: Fetch the list of verified companies engaging with your tracking pixel on specific domains.
- Visitor Analytics: Drill into session specifics of organizations interacting behind the scenes.
- Sales Pipeline: Identify key B2B traffic and prioritize new cold email targets or warm follow-ups immediately.
The Leadfeeder MCP Server exposes 9 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 Leadfeeder to Pydantic AI via MCP
Follow these steps to integrate the Leadfeeder 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 9 tools from Leadfeeder with type-safe schemas
Why Use Pydantic AI with the Leadfeeder MCP Server
Pydantic AI provides unique advantages when paired with Leadfeeder 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 Leadfeeder integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Leadfeeder connection logic from agent behavior for testable, maintainable code
Leadfeeder + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Leadfeeder MCP Server delivers measurable value.
Type-safe data pipelines: query Leadfeeder with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Leadfeeder tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Leadfeeder and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Leadfeeder responses and write comprehensive agent tests
Leadfeeder MCP Tools for Pydantic AI (9)
These 9 tools become available when you connect Leadfeeder to Pydantic AI via MCP:
get_account
Get details for a specific Leadfeeder account
get_custom_feed
Get details for a specific custom feed filter
get_lead
Get details for a specific lead
get_tracking_script
Get the tracking script for the account
list_account_visits
Get aggregate visits data across the entire account
list_accounts
Retrieve a list of accounts from Leadfeeder
list_custom_feeds
Retrieve the custom feeds active within a specific account
list_lead_visits
Get the website visits directly associated with a specific lead
list_leads
Retrieve a list of discovered leads within an account
Example Prompts for Leadfeeder in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Leadfeeder immediately.
"Analyze and list all identified corporate visitors targeting my site."
"Are there any manufacturing sector companies viewing our price points?"
"Highlight repeat prospects viewing documentation sections."
Troubleshooting Leadfeeder MCP Server with Pydantic AI
Common issues when connecting Leadfeeder to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiLeadfeeder + Pydantic AI FAQ
Common questions about integrating Leadfeeder 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.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Leadfeeder with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Leadfeeder to Pydantic AI
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.