How to Use the ZipRecruiter MCP in Pydantic AI

Q: How do I use ZipRecruiter with Pydantic AI?

You call ziprecruitersearchjobs and pass the necessary parameters. Because of Pydantic's validation, you know the job listing data will be correct.

Q: If I need job data from ZipRecruiter with Pydantic AI, how do I maintain correctness?

You use ziprecruitersearchjobs. The runtime validation guarantees that the output structure is correct, eliminating hallucinated fields.

Get reliable data from job searches using your Pydantic AI agent.

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Connect ZipRecruiter MCP to Pydantic AI

Create your Vinkius account to connect ZipRecruiter to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup ZipRecruiter with Pydantic AI

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Validate Job Searches via MCP Server

When you call `ziprecruiter_search_jobs`, every field is validated against a strict schema. The tool requires keywords, location, and salary data to run the search. This means if ZipRecruiter sends back unexpected fields or formats, your agent fails loudly with an error. You never get silent corruption.

Guaranteed Data Integrity

The `ziprecruiter_search_jobs` function ensures that the job listings you receive are correct and structured exactly how you expect them to be. This is critical for production code. It lets your agent focus on the logic, knowing that the data coming in—whether it's a salary or a title—is type-safe.

Precise Data Gathering

Use this tool to define exactly what you are looking for: specific keywords, target locations, and minimum pay. The validation layer makes sure these inputs map cleanly. This process removes the guesswork from job searching, giving you predictable output every time you run it.

Setup guide

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

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

result = await agent.run("List recent ZipRecruiter 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 ZipRecruiter. 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 ZipRecruiter MCP in Pydantic AI

You call `ziprecruiter_search_jobs` and pass the necessary parameters. Because of Pydantic's validation, you know the job listing data will be correct.

Yes. It handles keywords, locations, and salary ranges simultaneously, making sure every piece of input is validated before searching ZipRecruiter.

You use `ziprecruiter_search_jobs`. The runtime validation guarantees that the output structure is correct, eliminating hallucinated fields.

The primary benefit is stability. If the underlying API changes unexpectedly, your agent doesn't break quietly; it throws a clear validation error.

It processes keywords, geographic locations, and salary ranges found within the raw job descriptions pulled from ZipRecruiter.

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