Bring Hiring Pipeline
to Vercel AI SDK
Learn how to connect Flatwork ATS to Vercel AI SDK 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 Vercel AI SDK?
The Vercel AI SDK gives every Flatwork ATS tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 8 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
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Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Flatwork ATS integration everywhere
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Built-in streaming UI primitives let you display Flatwork ATS tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Flatwork ATS in Vercel AI SDK
Flatwork ATS and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Flatwork ATS to Vercel AI SDK 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 Vercel AI SDK
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 Vercel AI SDK 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 Vercel AI SDK
Every tool call from Vercel AI SDK 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 the Vercel AI SDK connect to MCP servers?
Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
Can I use MCP tools in Edge Functions?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp