Mav MCP Server for Pydantic AIGive Pydantic AI instant access to 9 tools to Create Lead, Get Lead, Get Playbook, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Mav 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 Mav app connector for Pydantic AI is a standout in the Human Resources category — giving your AI agent 9 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 Mav "
"(9 tools)."
),
)
result = await agent.run(
"What tools are available in Mav?"
)
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 Mav MCP Server
Connect your Mav AI recruiting account to any AI agent and manage candidate screening through natural conversation.
Pydantic AI validates every Mav 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
- Candidate Screening — Trigger automated AI screening conversations
- SMS Campaigns — Launch and manage outbound SMS recruiting campaigns
- Lead Management — Browse candidates and their qualification status
- Engagement Tracking — Monitor open rates, reply rates, and drop-offs
- Interview Data — Access responses and screening transcripts
The Mav 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.
All 9 Mav tools available for Pydantic AI
When Pydantic AI connects to Mav through Vinkius, your AI agent gets direct access to every tool listed below — spanning ai-recruiting, candidate-screening, sms-engagement, 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.
Create a lead and trigger a playbook
Get details for a specific lead
Get details for a specific playbook
List recent activities/events
List all leads
List all available Mav playbooks
Manually opt-out a lead
Stop a running playbook for a lead
Update an existing lead
Connect Mav to Pydantic AI via MCP
Follow these steps to wire Mav 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 Mav MCP Server
Pydantic AI provides unique advantages when paired with Mav 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 Mav integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Mav connection logic from agent behavior for testable, maintainable code
Mav + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Mav MCP Server delivers measurable value.
Type-safe data pipelines: query Mav with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Mav tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Mav and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Mav responses and write comprehensive agent tests
Example Prompts for Mav in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Mav immediately.
"Show active SMS campaigns and completion rates."
"Launch a screening campaign for the new Warehouse Staff list."
"Show screening results and transcripts for qualified candidates."
Troubleshooting Mav MCP Server with Pydantic AI
Common issues when connecting Mav to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiMav + Pydantic AI FAQ
Common questions about integrating Mav 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.