How to Use the AirMatch Pro MCP in Pydantic AI

Get type-safe candidate matching and pipeline management using Pydantic AI with AirMatch Pro.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect AirMatch Pro MCP to Pydantic AI

Create your Vinkius account to connect AirMatch Pro to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup AirMatch Pro with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-safe lead ingestion via Pydantic AI

Stop worrying about corrupted recruiting data crashing your pipeline. Your Pydantic AI agent validates every payload from `list_leads` and `get_lead` against your strict Python schemas at runtime. This MCP Server setup fails immediately if the API returns unexpected fields or missing values. This guarantees that your agent never processes malformed candidate profiles.

Validate proposals and estimates before writing

Ensure every sales document conforms exactly to your internal data models. Your agent uses `create_proposal` to write new agreements, but only after validating the parameters against your Pydantic schemas. You can inspect active structures safely using `get_proposal` and `list_estimates`. Because Pydantic AI enforces strict types, your agent won't hallucinate pricing fields or contract terms.

Secure pipeline monitoring and customer audits

Maintain clean relationship records without manual schema checking. Your agent checks account details via `list_customers` and pulls active roles using `list_jobs` with guaranteed type safety. The agent runs `check_airmatch_status` to verify the connection, then queries your recruiter account with `get_profile`. Every field maps directly to type-hinted Python classes.

Setup guide

Set up AirMatch Pro MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "airmatch-pro-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to AirMatch Pro tools.",
)

result = await agent.run("List recent AirMatch Pro transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AirMatch Pro. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect AirMatch Pro now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about AirMatch Pro MCP in Pydantic AI

The framework wraps the AirMatch Pro tool outputs in Pydantic models. If a tool like `get_lead` returns data that violates your schema, the agent catches the error immediately instead of passing bad data downstream.

Yes. Pydantic AI is model-agnostic, meaning you can run your AirMatch Pro MCP Server workflows using local models or commercial APIs while maintaining strict type validation.

Use the unified MCPToolset constructor pointing to your Vinkius MCP Server HTTP endpoint, then pass the toolset directly to your Pydantic AI agent.

Your agent raises a validation or connection error that you can handle gracefully in your Python code, preventing silent failures during automated recruiting runs.

All estimates and proposals are validated purely in memory within your Python runtime. The Vinkius MCP Server handles data in transit using TLS, ensuring no sensitive financial or candidate data is cached or exposed.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript