How to Use the Greenhouse Alternative MCP in Pydantic AI

Q: How do I configure Greenhouse Alternative with Pydantic AI?

You initialize MCPToolset pointing to your Vinkius HTTP endpoint. This unified approach replaces deprecated transports and exposes tools like listapplications to your agent.

Q: How do I track partner referrals using this MCP Server?

Your agent runs getpartnercandidates to verify referral statuses, validating the output against your custom Pydantic schemas. This guarantees clean tracking across all external sourcing partners.

Run type-safe recruiting automation. Connect Pydantic AI to Greenhouse Alternative for validated candidate pipeline updates.

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Connect Greenhouse Alternative MCP to Pydantic AI

Create your Vinkius account to connect Greenhouse Alternative 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 Greenhouse Alternative with Pydantic AI

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Type-safe candidate application updates

The `update_application` tool modifies candidate records while Pydantic AI enforces strict runtime validation on every field. If the recruitment API returns an unexpected data type, your pipeline fails loudly instead of saving corrupt candidate info. This strict validation applies when your agent runs `get_application` to pull candidate files. You will never have to deal with missing null fields or broken schemas silently breaking your downstream LLM prompts.

Clean job board querying with this MCP Server

The `get_board_job` tool pulls structured job post details, including custom application questions, directly into your Pydantic schemas. Your Pydantic AI agent parses these questions to prepare candidates for specific interview loops. To keep your internal database synchronized, the agent calls `list_board_jobs` to verify active listings. Candidate-facing agents will never accidentally recommend closed or outdated positions.

Validate partner candidate submissions

The `submit_partner_candidate` tool registers external referrals while validating their contact details against strict Pydantic models. Every resume pushed by external partners must contain required fields like email and phone number. Once the candidate is validated, the agent runs `add_application_to_candidate` to link them to active roles. Our MCP Server handles the database sync dynamically, so your ATS database stays perfectly clean and formatted without manual oversight.

Setup guide

Set up Greenhouse Alternative 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": {
        "greenhouse-alternative-1-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Greenhouse Alternative MCP in Pydantic AI

Pydantic AI raises a validation error instantly, preventing your agent from processing corrupted candidate profiles. This keeps your ATS data clean and prevents silent pipeline failures.

You initialize `MCPToolset` pointing to your Vinkius HTTP endpoint. This unified approach replaces deprecated transports and exposes tools like `list_applications` to your agent.

Yes, every tool schema is mapped directly to Pydantic models at runtime. Destructive actions like `delete_application` are strictly validated before they run against your recruitment API.

Your agent runs `get_partner_candidates` to verify referral statuses, validating the output against your custom Pydantic schemas. This guarantees clean tracking across all external sourcing partners.

All candidate PII, application records, and audit logs are processed via ephemeral V8 Isolate sandboxes. Vinkius handles the underlying token authentication, ensuring candidate data is never persisted on external servers.

Use it with your favorite AI tools

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