Bring Candidate Tracking
to Google ADK
Learn how to connect Greenhouse to Google ADK and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the 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.
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
How it works
1. Subscribe to this server
2. Retrieve your Harvest API Key from Greenhouse (Configure > Dev Center > API Credential Management)
3. Note a valid User ID to perform actions 'On-Behalf-Of' for auditing purposes
4. Start managing your talent acquisition from Claude, Cursor, or any MCP client
No more manual status updates or digging through candidates in the ATS. Your AI acts as your dedicated recruitment coordinator.
Who is this for?
- Recruiters & Sources — instantly identify candidate statuses and advance top talent through the pipeline using natural language
- Hiring Managers — retrieve job opening details and department structures without leaving your planning tools
- HR Operations — manage office locations and department organization through automated queries
Built-in capabilities (12)
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
Why Google ADK?
Google ADK natively supports Greenhouse as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 12 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
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Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Greenhouse
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Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
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Seamless integration with Google Cloud services means you can combine Greenhouse tools with BigQuery, Vertex AI, and Cloud Functions
Greenhouse in Google ADK
Greenhouse and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Greenhouse to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Greenhouse in Google ADK
The Greenhouse 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. All 12 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Greenhouse for Google ADK
Every tool call from Google ADK to the Greenhouse MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
What is the 'On-Behalf-Of' requirement?
Greenhouse requires write operations to be associated with a specific User ID for auditing. This ID is passed in the header to identify who performed the action.
Can I search for candidates by email?
Yes! Use the list_candidates tool and provide the email parameter to find a specific person's recruitment record and history.
How do I advance an application to the next stage?
The advance_application tool requires a valid application ID. It will automatically move the candidate to the next sequential stage defined in your job's workflow.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk