How to Use the USAJOBS (OPM) MCP in Pydantic AI

Q: What is the best way to get job codes for USAJOBS (OPM) using Pydantic AI?

You use getcodelist first. Since this tool provides clean values and codes, your agent can reliably build highly specific search queries before running a main job search.

Q: Can Pydantic AI handle large datasets from USAJOBS (OPM)?

Yes, the gethistoricjoas tool supports pagination via continuation token. Your agent can process enormous archives of historical job postings while maintaining type-safe data integrity.

Get guaranteed correct USAJOBS (OPM) job data using Pydantic AI.

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Connect USAJOBS (OPM) MCP to Pydantic AI

Create your Vinkius account to connect USAJOBS (OPM) 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 USAJOBS (OPM) with Pydantic AI

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Search Jobs with Guaranteed Schema

Need to find active openings? Run `search_jobs` through the MCP Server. Because every response is validated against Pydantic models, you know exactly what fields you're getting back. If USAJOBS (OPM) returns unexpected data, your agent fails loudly with a validation error—no silent corruption.

Extract Full Job Descriptions

The `get_announcement_text` tool pulls the complete text for current or past job listings. This is crucial because you need the full details, not just a summary. Pydantic validation ensures that even these large text fields conform to your expected data structure.

Bulk Data Retrieval with Strong Types

Use `get_historic_joas` for bulk data. Its support for pagination means you can process massive archives, and Pydantic validation guarantees the structural integrity of every record. It makes handling historical USAJOBS (OPM) data reliable.

Setup guide

Set up USAJOBS (OPM) 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": {
        "usajobs-opm-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent USAJOBS (OPM) 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 USAJOBS. 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 USAJOBS (OPM) MCP in Pydantic AI

Pydantic validation checks every single response from the MCP Server. If `search_jobs` returns a field that doesn't match your defined schema, the agent fails immediately, preventing bad data downstream.

You use `get_code_list` first. Since this tool provides clean values and codes, your agent can reliably build highly specific search queries before running a main job search.

Yes, the `get_historic_joas` tool supports pagination via continuation token. Your agent can process enormous archives of historical job postings while maintaining type-safe data integrity.

The MCP Server touches Job Announcement Text and structured code values. The strong typing helps you define exactly how these sensitive employment records should be handled and processed.

You'll rely on the type-safe structure. When you get active listings via `search_jobs`, the agent validates that every returned record has the expected fields, making your whole pipeline rock solid.

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