How to Use the Jobtoolz MCP in Pydantic AI

Build type-safe recruitment agents using Pydantic AI to validate every Jobtoolz candidate and job payload at runtime.

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Connect Jobtoolz MCP to Pydantic AI

Create your Vinkius account to connect Jobtoolz 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.

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Setup Jobtoolz with Pydantic AI

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Validate candidate payloads with Pydantic AI

This MCP Server integrates `get_candidate` and `list_candidates` directly into your type-safe agent workflows. Pydantic AI enforces strict runtime validation on every candidate field returned by the API. If a candidate record has missing contact details or corrupted history, the agent catches it instantly. This prevents your downstream recruitment pipelines from processing broken or incomplete profiles. You write clean code knowing that the data matching your schema is guaranteed to be correct.

Enforce job schemas across departments

This MCP Server relies on `get_job` and `list_jobs` to feed validated role data to your models. The agent map-checks job descriptions, departments, and requirements against your internal Pydantic models. You will never have to worry about a model hallucinating a non-existent job ID. Combine this with `list_departments` to ensure every job is assigned to a valid, active business unit. It keeps your organizational structure clean and free of data entry errors.

Verify hiring stages and tags in real time

This MCP Server exposes `list_stages` and `list_tags` to keep your automated workflows aligned with your actual ATS setup. Your agent validates that candidates are only moved to valid stages in your pipeline. It eliminates the risk of running actions on deprecated tags or stages. You can also query `list_locations` and `list_users` to verify office assignments and hiring manager details. Every single response is strictly typed, so your code fails loudly if the API structure changes.

Setup guide

Set up Jobtoolz 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": {
        "jobtoolz-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Jobtoolz. 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.

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Common questions about Jobtoolz MCP in Pydantic AI

Use the MCP toolset class to connect to your Vinkius HTTP endpoint. Pass this toolset into your Agent constructor using the toolsets argument. The framework automatically registers all 10 recruitment tools for your model.

The framework raises a validation error immediately rather than passing corrupted data to your model. If `get_candidate` returns a field that violates your schema, the execution halts. This protects your database from bad writes.

Yes, the framework supports both transport protocols. You connect to your externally running Vinkius server using the unified toolset interface. This ensures fast, reliable communication for all your recruitment queries.

Yes, Pydantic AI is model-agnostic. You can run local models or commercial APIs alongside the Jobtoolz tools. The framework handles tool calling and validation identically across all supported LLM providers.

Your candidate files and job descriptions are processed inside secure, isolated V8 sandboxes. Vinkius handles the authentication token securely and executes calls in ephemeral environments. No recruitment data is ever logged or stored persistently.

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