Greenhouse MCP Server
Connect to the Greenhouse MCP server to manage candidates and applications, schedule interviews, read scorecards, and download resumes across your hiring pipeline using AI agents on Gumloop, Claude, or Cursor.
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Greenhouse
Installation
Get StartedCreate a Gumloop Account
To use this MCP, you need a Gumloop account. If you don't have one yet, you can create one for free.
Copy Your Server URL
Copy your MCP server URL and add it to your client. You'll be prompted to authorize on first use.
Tools (37)
List Candidates
List candidates in your Greenhouse account with filtering options and automatic pagination support.
List Candidate Activity
List recent Greenhouse activity metadata for one candidate from Harvest v3 notes. Returns only type, created_at, and subject; note bodies and email contents are never returned.
Create Candidate
Create a new candidate in your Greenhouse account.
Update Candidate
Update an existing candidate in your Greenhouse account.
Delete Candidate
Delete a candidate permanently from your Greenhouse account.
Anonymize Candidate
Anonymize a candidate's information in your Greenhouse account.
Merge Candidates
Merge two candidates in your Greenhouse account.
List Applications
List applications in your Greenhouse account with filtering options and automatic pagination support.
List Application Activity
List recent Greenhouse activity metadata for one application from Harvest v3 notes. Returns only type, created_at, and subject; note bodies and email contents are never returned.
Reject Application
Reject an application in your Greenhouse account.
Unreject Application
Unreject a previously rejected application in your Greenhouse account.
Hire Application
Mark an application as hired in your Greenhouse account.
What is Greenhouse MCP?
The Greenhouse MCP server gives AI agents access to your Greenhouse applicant tracking system. That means agents can manage candidates, drive applications through your pipeline, schedule and reschedule interviews, read scorecards and interviewer feedback, update jobs and review job posts, collaborate with job notes, download resumes and attachments, and audit organizational data like users and departments. It works across the Greenhouse Harvest API, so an AI agent can both answer questions about your hiring and take action using the information it gets.
If your recruiting team spends time moving candidates between stages by hand, coordinating interview times over email, or digging through scorecards to assemble debriefs, an AI agent can take over a lot of that busywork. Describe what you need, and your AI agent will handle recruiting operations for you.
MCP stands for Model Context Protocol. It’s an open standard that gives AI agents a way to connect to external tools and services. Instead of registering Harvest API credentials, handling pagination and rate limits, and writing code against the Greenhouse API, you connect your Greenhouse account once. After that, you manage your hiring pipeline just by asking your AI agent in plain language.
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What you can do with Greenhouse MCP on Gumloop
Manage candidates end to end
Create candidates with full contact details, tags, and custom fields, update their records, merge duplicates into a single profile, and anonymize specific fields for GDPR requests. Your AI agent keeps candidate data clean without manual edits in Greenhouse.
Drive applications through your pipeline
List applications with rich filters, then move applications between stages, transfer them to other jobs, reject (with a reason and optional email) or unreject, and mark them hired. An agent can advance candidates based on rules you set.
Schedule and manage interviews
Create interviews with specific interviewers, times, locations, and video conferencing URLs, reschedule or update them as plans change, and cancel when needed. View each interviewer’s response status to keep coordination on track.
Read scorecards and interviewer feedback
Pull submitted scorecards, the questions behind them, interviewer answers and selected options, and candidate attribute ratings. Your agent can roll feedback into a clean debrief or surface where interviewers disagreed. (Scorecards are read-only.)
Monitor jobs and pipeline stages
List open, draft, or closed jobs, update job metadata like name, offices, department, and custom fields, review live and internal job posts, and browse the interview stages configured for each job.
Collaborate with job notes
Create, edit, and delete internal notes on a job, with visibility controls for admin-only or private notes. Keep hiring context in one place for the team.
Download resumes and attachments
List resumes, cover letters, and offer packets on a candidate or application, and pull them into Gumloop storage so an AI agent can parse, summarize, or match them.
Audit organizational data
Browse users, departments, approvers, and interviewers with detailed filters. Useful for routing, reporting prep, and keeping hiring workflows accurate.
How to connect the Gumloop Greenhouse MCP Server
- 1
Create a free Gumloop account
Sign up at gumloop.com. No credit card required.
- 2
Add the Greenhouse MCP server
Copy your MCP server URL from Gumloop and add it to your preferred client (Claude, Cursor, or Gumloop workflows). You'll authorize on first use.
- 3
Start using Greenhouse in your AI workflows
That's it. Your AI agent can now manage candidates and applications, schedule interviews, and read scorecards across your Greenhouse account. Use it inside a Gumloop automation, in Claude Desktop, or in Cursor.
Greenhouse MCP use cases
Automated pipeline management for recruiters
An AI agent can read applications by stage and job, move candidates forward based on scorecard ratings, reject with the right reason and a templated email, and mark hires as they close. Recruiters spend less time on pipeline mechanics and more on candidates.
Interview scheduling and coordination
Read a job’s interview stages, create interviews with the right interviewers, times, locations, and video links, and reschedule or cancel as calendars shift. When something changes, the agent updates the interview and can notify everyone through another tool like Slack or Gmail.
Resume screening at volume
Pull resumes and cover letters into Gumloop storage, have an AI agent read each one against the job’s criteria, then tag the candidate, set custom fields, or move the application accordingly. Hiring teams review a ranked shortlist instead of a stack of PDFs.
Hiring debriefs and scorecard analysis
After interviews wrap, an AI agent can pull every scorecard, answer, and candidate attribute rating for an application and compile a single balanced debrief, including where interviewers agreed and disagreed, ahead of the decision meeting.
Candidate data hygiene and GDPR requests
Keep your database clean by merging duplicate candidates into one record, and handle right-to-be-forgotten requests by anonymizing specific candidate fields. An agent can run these on request or on a schedule.
Why use Gumloop for Greenhouse MCP
No API key, no Dev Center setup
Building your own Greenhouse MCP server means setting up Harvest API credentials, handling OAuth or key rotation, and writing code against the API’s pagination and rate limits. Instead, Gumloop can handle all of that for you. Click Connect, authorize once, and your token refreshes automatically.
Works with multiple MCP clients
Use the Greenhouse MCP server endpoint in Claude Desktop, Cursor, or directly inside Gumloop. Same server URL, works with any MCP client.
Chain Greenhouse with 100+ other integrations
Combine Greenhouse with Slack, Gmail, Google Calendar, and other MCP tools in a single AI agent. Notify a channel when someone is hired, sync interview times to a calendar, or kick off onboarding the moment an offer closes.
Enterprise-grade and scalable
Built for teams, with role-based permissions and dedicated support for Pro users. The Greenhouse MCP respects your existing access controls, so an agent only reaches what your connected account can, and candidate PII stays protected.
Pricing includes a free plan
You can test the Greenhouse MCP integration on Gumloop’s free tier before committing. Paid plans start at $37/month.
Frequently asked questions
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