Bring Feature Flags
to Vercel AI SDK
Learn how to connect ConfigCat to Vercel AI SDK and start using 18 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 ConfigCat MCP Server?
Connect ConfigCat to any AI agent to streamline your feature flag management and release workflows through natural conversation.
What you can do
- Configurations & Environments — List, create, and manage configuration containers and environments (Test, Staging, Production) across your products.
- Feature Flags & Settings — Create and inspect feature flags or settings (boolean, string, int, double) to control application logic.
- Value Management — Retrieve and update setting values dynamically to trigger real-time changes in your software without redeploying.
- Segment Control — Manage user segments to target specific groups for canary releases or A/B testing.
How it works
- Subscribe to this server
- Enter your ConfigCat API Key ID and Secret
- Start managing your feature toggles from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Developers — toggle features and check flag statuses directly from the code editor to maintain focus.
- DevOps Engineers — manage environments and configurations as part of the CI/CD workflow via automated agents.
- Product Managers — oversee feature rollouts and user segments through simple chat commands without technical overhead.
Built-in capabilities (18)
Create a new configuration
Create a new environment
Create a new segment
Create a new feature flag or setting
Delete a configuration
Delete an environment
Delete a segment
Delete a setting
Get details of a specific configuration
Get details of an environment
Get details of a segment
Get details of a setting
Get the value of a setting in an environment
List all configurations in a product
g., Test, Production) for a specific product. List all environments in a product
List all segments in a product
List all settings in a configuration
Update the value/targeting of a setting
Why Vercel AI SDK?
The Vercel AI SDK gives every ConfigCat tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 18 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
- —
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same ConfigCat integration everywhere
- —
Built-in streaming UI primitives let you display ConfigCat 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
ConfigCat in Vercel AI SDK
ConfigCat and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect ConfigCat 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 ConfigCat in Vercel AI SDK
The ConfigCat 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 18 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
ConfigCat for Vercel AI SDK
Every tool call from Vercel AI SDK to the ConfigCat MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I list all feature flags in a specific configuration?
Yes. Use the list_settings tool with your Configuration ID to retrieve all feature flags and settings, including their types and keys.
How do I create a new environment like 'Staging'?
Simply use the create_environment tool. Provide the Product ID and the name 'Staging' to instantly set up a new environment for your flags.
Is it possible to update the value of a setting remotely?
Yes! The update_setting_value tool allows you to change the value of any flag or setting for a specific environment in real-time.
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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