Bring Technical Assessment
to Vercel AI SDK
Learn how to connect Qualified.io to Vercel AI SDK and start using 20 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Qualified.io MCP Server?
Connect your Qualified.io account to any AI agent to streamline your technical recruitment and engineering assessment workflows through natural conversation.
What you can do
- Assessment Management — List, create, and manage the lifecycle of your coding assessments, including publishing and archiving.
- Candidate Invitations — Send assessment invitations to candidates and manage active invites directly through the API.
- Result Tracking — Retrieve detailed assessment results and streamlined exhibits to evaluate candidate performance instantly.
- Lifecycle Control — Terminate active results or schedule retries for candidates who need another attempt.
- Cohort Analysis — List and organize assessment cohorts to manage groups of candidates effectively.
How it works
- Subscribe to this server
- Enter your Qualified.io API Key
- Start managing your technical hiring pipeline from Claude, Cursor, or any MCP-compatible client
No more jumping between your ATS and assessment platform to check if a candidate has finished their test. Your AI acts as a technical recruiting coordinator.
Who is this for?
- Engineering Managers — quickly review candidate scores and code exhibits without leaving the dev environment.
- Technical Recruiters — automate the process of inviting candidates and checking status updates.
- Talent Operations — manage large cohorts and assessment versions with simple natural language commands.
Built-in capabilities (20)
Archive an assessment
Cancel an assessment invitation
Create a new assessment
Create a review for an assessment result
Retrieve a specific assessment
Retrieve a specific assessment result
Retrieve streamlined exhibit data for an assessment result
Retrieve a specific challenge
Invite candidates to take an assessment
Invite candidates via a cohort
List assessment cohorts
List assessment results
List assessments
List challenges
Publish an assessment
Schedule a retry (reopen/retake) for an assessment result
Terminate an assessment result
Unarchive an assessment
Unpublish an assessment
Update a review for an assessment result
Why Vercel AI SDK?
The Vercel AI SDK gives every Qualified.io tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 20 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
- —
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Qualified.io integration everywhere
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Built-in streaming UI primitives let you display Qualified.io 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
Qualified.io in Vercel AI SDK
Qualified.io and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Qualified.io 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 | 4,000+ 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 Qualified.io in Vercel AI SDK
The Qualified.io 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 20 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
Qualified.io for Vercel AI SDK
Every tool call from Vercel AI SDK to the Qualified.io MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see a summary of a candidate's test performance without pulling the full raw data?
Yes. Use the get_assessment_result_exhibit tool. It provides a streamlined view of the candidate's performance, making it easier for your AI to summarize the results for you.
How do I invite multiple candidates to a specific assessment at once?
You can use the invite_candidates tool. Simply provide the assessment ID and the candidate data payload, and the server will handle the invitations through the Qualified.io API.
Is it possible to reopen a test for a candidate who had technical issues?
Yes, you can use the schedule_retry_assessment_result tool with the specific Result ID to allow the candidate to retake or continue their assessment.
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
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