Bring Hiring Pipeline
to Google ADK
Learn how to connect Flatwork ATS to Google ADK and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for Subscribers
What is the Flatwork ATS MCP Server?
Connect your Flatwork ATS account to any AI agent and take full control of your recruitment pipeline and candidate management workflows through natural conversation.
What you can do
- Job Orchestration — List all open and closed job postings and retrieve detailed metadata, including hiring teams and job requirements programmatically
- Candidate Tracking — Manage your complete directory of applicants and retrieve detailed profiles and contact information programmatically
- Application Lifecycle — Monitor active job applications and update candidate hiring stages (Interview, Hired, Rejected) directly through your agent
- Applicant Discovery — Programmatically create new candidates in the system using external data to automate your sourcing pipeline
- System Monitoring — List configured webhooks to understand real-time data flows and ensure high-fidelity synchronization with your HR tools
How it works
1. Subscribe to this server
2. Retrieve your API Key from Flatwork ATS (Settings > API)
3. Start managing your hiring pipeline from Claude, Cursor, or any MCP client
No more manual status checking or digging through candidate lists. Your AI acts as your dedicated talent acquisition and recruitment coordinator.
Who is this for?
- Recruiters & HR Managers — instantly check application statuses and update hiring stages using natural language commands
- Talent Acquisition Teams — automate candidate registration from external sources and monitor job posting activity without leaving your workspace
- Hiring Managers — retrieve candidate profiles and job details through simple AI queries to prepare for interviews
Built-in capabilities (8)
Pass applicant data as a JSON string. Add a new candidate
Get applicant details
Get job details
List all applicants/candidates
List all job applications
List all job postings
List configured webhooks
Update application hiring stage
Why Google ADK?
Google ADK natively supports Flatwork ATS as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 8 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 Flatwork ATS
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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 Flatwork ATS tools with BigQuery, Vertex AI, and Cloud Functions
Flatwork ATS in Google ADK
Flatwork ATS and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Flatwork ATS 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 Flatwork ATS in Google ADK
The Flatwork ATS 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 8 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
Flatwork ATS for Google ADK
Every tool call from Google ADK to the Flatwork ATS MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find my Flatwork API Key?
Log in to your Flatwork account, navigate to Settings > API, and generate or copy your unique secret key.
Can I move a candidate to a custom hiring stage?
Yes! Use the update_application_status tool and provide the string name of your custom stage as defined in your ATS workflow.
How do I add new candidates found via LinkedIn?
Use the create_applicant tool and pass a JSON string containing the candidate's details like first name, last name, and email address.
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