Airbyte Greenhouse Connector for AI platforms
Project description
Greenhouse agent connector
Greenhouse is an applicant tracking system (ATS) that helps companies manage their hiring process. This connector provides access to candidates, applications, jobs, offers, users, departments, offices, job posts, sources, and scheduled interviews for recruiting analytics and talent acquisition insights.
Example questions
The Greenhouse connector is optimized to handle prompts like these.
- Show me candidates from {company} who applied last month
- What are the top 5 sources for our job applications this quarter?
- List all open jobs in the Sales department
- Analyze the interview schedules for our engineering candidates this week
- Get details of recent job offers for {team_member}
- Compare the number of applications across different offices
- Identify candidates who have multiple applications in our system
- Show me upcoming scheduled interviews for our marketing positions
- Summarize the candidate pipeline for our latest job posting
- Find the most active departments in recruiting this month
Unsupported questions
The Greenhouse connector isn't currently able to handle prompts like these.
- Create a new job posting for the marketing team
- Schedule an interview for {candidate}
- Update the status of {candidate}'s application
- Delete a candidate profile
- Send an offer letter to {candidate}
- Edit the details of a job description
Installation
uv pip install airbyte-agent-greenhouse
Usage
Connectors can run in open source or hosted mode.
Open source
In open source mode, you provide API credentials directly to the connector.
from airbyte_agent_greenhouse import GreenhouseConnector
from airbyte_agent_greenhouse.models import GreenhouseAuthConfig
connector = GreenhouseConnector(
auth_config=GreenhouseAuthConfig(
api_key="<Your Greenhouse Harvest API Key from the Dev Center>"
)
)
@agent.tool_plain # assumes you're using Pydantic AI
@GreenhouseConnector.tool_utils
async def greenhouse_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
Hosted
In hosted mode, API credentials are stored securely in Airbyte Cloud. You provide your Airbyte credentials instead.
This example assumes you've already authenticated your connector with Airbyte. See Authentication to learn more about authenticating. If you need a step-by-step guide, see the hosted execution tutorial.
from airbyte_agent_greenhouse import GreenhouseConnector
connector = GreenhouseConnector(
external_user_id="<your_external_user_id>",
airbyte_client_id="<your-client-id>",
airbyte_client_secret="<your-client-secret>"
)
@agent.tool_plain # assumes you're using Pydantic AI
@GreenhouseConnector.tool_utils
async def greenhouse_execute(entity: str, action: str, params: dict | None = None):
return await connector.execute(entity, action, params or {})
Full documentation
This connector supports the following entities and actions.
| Entity | Actions |
|---|---|
| Candidates | List, Get |
| Applications | List, Get |
| Jobs | List, Get |
| Offers | List, Get |
| Users | List, Get |
| Departments | List, Get |
| Offices | List, Get |
| Job Posts | List, Get |
| Sources | List |
| Scheduled Interviews | List, Get |
| Application Attachment | Download |
| Candidate Attachment | Download |
For all authentication options, see the connector's authentication documentation.
For detailed documentation on available actions and parameters, see this connector's full reference documentation.
For the service's official API docs, see the Greenhouse API reference.
Version information
- Package version: 0.17.64
- Connector version: 0.1.4
- Generated with Connector SDK commit SHA: 71f48c102ce98c9298e5102761e740f0d97eb71b
Project details
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