Greenhouse MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Advance Application, Create Candidate, Get Api Status, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Greenhouse through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Greenhouse app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Greenhouse "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Greenhouse?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Greenhouse MCP Server
Connect your Greenhouse account to any AI agent and take full control of your hiring pipeline and recruitment workflows through natural conversation.
Pydantic AI validates every Greenhouse tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Candidate Orchestration — List and manage candidate records programmatically, including contact info, current company, and professional titles
- Application Lifecycle — Monitor job applications and take immediate action by advancing candidates to the next stage or marking rejections with reasons
- Job Management — Access detailed metadata for all active job openings, including hiring teams and department structures
- Organizational Visibility — Retrieve complete company department lists and office locations to coordinate recruitment logistics
- System Monitoring — Check API connectivity and Harvest API status directly through your agent for reliable data operations
The Greenhouse MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Greenhouse tools available for Pydantic AI
When Pydantic AI connects to Greenhouse through Vinkius, your AI agent gets direct access to every tool listed below — spanning candidate-tracking, hiring-pipeline, talent-acquisition, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Move candidate to next stage
Can include first name, last name, and company. Add new candidate
Get account connectivity
Get candidate info
Get job metadata
List job applications
List recruitment candidates
List company departments
List office locations
List active job openings
Requires a reason ID. Reject job application
Modify candidate info
Connect Greenhouse to Pydantic AI via MCP
Follow these steps to wire Greenhouse into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Greenhouse MCP Server
Pydantic AI provides unique advantages when paired with Greenhouse through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Greenhouse integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Greenhouse connection logic from agent behavior for testable, maintainable code
Greenhouse + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Greenhouse MCP Server delivers measurable value.
Type-safe data pipelines: query Greenhouse with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Greenhouse tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Greenhouse and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Greenhouse responses and write comprehensive agent tests
Example Prompts for Greenhouse in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Greenhouse immediately.
"Find candidate with email 'candidate@example.com' and show their status."
"List all active job openings for the 'Engineering' department."
"Advance application ID 'app_987' to the next stage."
Troubleshooting Greenhouse MCP Server with Pydantic AI
Common issues when connecting Greenhouse to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiGreenhouse + Pydantic AI FAQ
Common questions about integrating Greenhouse MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.