Compatible with every major AI agent and IDE
What is the Unleash (Feature Toggles) MCP Server?
Connect your Unleash instance to any AI agent and gain full control over your feature management lifecycle through natural conversation.
What you can do
- Feature Evaluation — Fetch all feature flags and strategies for server-side evaluation or evaluate specific flags for client-side contexts using User IDs and properties.
- Project & Environment Audit — List all Unleash projects, environments, and segments to understand your infrastructure layout.
- Flag Management — Inspect all feature flags within specific projects to verify rollout statuses and strategy configurations.
- Metrics & Registration — Report SDK usage metrics and register new client or frontend instances directly through the agent.
- User Management — Retrieve lists of users and segments to verify targeting rules and access.
How it works
- Subscribe to this server
- Enter your Unleash API URL and API Token (Admin, Client, or Frontend depending on your needs)
- Start managing your feature rollouts from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps & SREs — quickly audit environments and segments without navigating the Unleash UI
- Product Managers — check the status of feature toggles and rollout strategies across different projects
- Software Engineers — verify flag evaluations and context properties directly from the code editor
Built-in capabilities (11)
Fetch all feature flags and strategies for server-side evaluation
Optionally provide context like userId or properties. Fetch enabled feature flags for a specific Unleash Context
Fetches all environments configured in Unleash. List all Unleash environments
Fetches features for a given project ID. List all feature flags in a specific project
Fetches all projects configured in Unleash. List all Unleash projects
Fetches all segments configured in Unleash. List all Unleash segments
Fetches all users configured in Unleash. List all Unleash users
Register a new backend SDK instance
Register a new frontend SDK instance
Report flag usage metrics from a backend SDK
Report flag usage metrics from a frontend SDK
Why Vercel AI SDK?
The Vercel AI SDK gives every Unleash (Feature Toggles) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 11 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
- —
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 Unleash (Feature Toggles) integration everywhere
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Built-in streaming UI primitives let you display Unleash (Feature Toggles) 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
Unleash (Feature Toggles) in Vercel AI SDK
Unleash (Feature Toggles) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Unleash (Feature Toggles) 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 Unleash (Feature Toggles) in Vercel AI SDK
The Unleash (Feature Toggles) 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 11 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
Unleash (Feature Toggles) for Vercel AI SDK
Every tool call from Vercel AI SDK to the Unleash (Feature Toggles) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I evaluate feature flags for a specific user ID?
Yes. Use the get_frontend_features tool and provide the userId. The agent will return the enabled flags based on the Unleash context for that specific user.
How do I see all feature flags associated with a specific project?
You can use the list_project_features tool by providing the projectId. This will list all toggles, their types, and current statuses within that project.
Does this server support listing segments and environments?
Yes, the server includes list_segments and list_environments tools, allowing you to audit your Unleash configuration and targeting rules easily.
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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