Bring Low Code
to Vercel AI SDK
Learn how to connect Fastn to Vercel AI SDK and start using 16 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 Fastn MCP Server?
Connect your Fastn account to any AI agent to orchestrate complex backend workflows and real-time API flows through natural language.
What you can do
- Flow Execution — Trigger Fastn flows instantly with custom JSON payloads and receive real-time responses via the API sync layer.
- Workflow Management — List, create, update, and publish flow definitions across different tenants to maintain your business logic.
- Execution Monitoring — Track execution history and drill down into step-by-step traces to debug or audit automated processes.
- Credential Handling — Securely store, retrieve, and rotate credentials for your various connectors and third-party integrations.
- Platform Insights — Monitor your platform usage, including daily quotas, summary metrics, and active space configurations.
How it works
- Subscribe to this server
- Provide your Fastn API Key and Space ID
- Start executing and managing your backend logic from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Developers — deploy, test, and trigger flows without leaving your code editor or terminal.
- DevOps Engineers — monitor execution traces and manage environment credentials programmatically through the agent.
- Product Teams — trigger business logic flows and check automation statuses via natural conversation.
Built-in capabilities (16)
Deactivate / archive a flow
Cancel a running execution
Create a new flow definition
The input object must match the Request Schema defined in the flow trigger. Execute a Fastn flow instantly (API Real-Time Sync)
Retrieve stored credentials
Get full step-by-step execution trace
Daily usage breakdown
Usage summary
Current usage against plan limits
Get a flow full specification
List execution history for a tenant
List all flow definitions for a tenant
Deploy / publish a flow
Rotate credentials
Store connector credentials
Update a flow definition
Why Vercel AI SDK?
The Vercel AI SDK gives every Fastn tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 16 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 Fastn integration everywhere
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Built-in streaming UI primitives let you display Fastn 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
Fastn in Vercel AI SDK
Fastn and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Fastn 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 Fastn in Vercel AI SDK
The Fastn 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 16 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
Fastn for Vercel AI SDK
Every tool call from Vercel AI SDK to the Fastn MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I trigger a flow and get the result immediately?
Yes. Use the execute_flow tool with the flow name and input data. It performs a real-time sync execution and returns the response directly to the agent.
How can I debug a failed flow execution?
You can use list_executions to find the ID of the failed run, then use get_execution to retrieve a full step-by-step trace of what happened during that specific execution.
Is it possible to update an existing workflow definition?
Absolutely. The update_workflow tool allows you to modify the JSON definition of any flow. Remember to use publish_workflow afterwards to deploy your changes to the live environment.
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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