Cognita (RAG Framework) MCP Server for Vercel AI SDK 7 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Cognita (RAG Framework) through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Cognita (RAG Framework), list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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
About Cognita (RAG Framework) MCP Server
Connect your Cognita (TrueFoundry) instance to any AI agent and take full control of your modular RAG workflows through natural conversation.
The Vercel AI SDK gives every Cognita (RAG Framework) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 7 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Knowledge Collections — List and audit RAG collections to inspect embedding configurations, token lengths, and parser details
- Data Ingestion — Force sync remote files from SQL, Cloud Storage, or APIs into your vector space to update your knowledge base
- RAG Queries — Dispatch automated AI questions that query your vector store and synthesize accurate answers from stored context
- Chunk Auditing — Perform lexical or semantic searches to pull raw document chunks and verify precise text segments
- Model Registry — Enumerate available LLMs and embedding models registered inside your modular Cognita installation
- DataSource Management — List all connected data sources to verify which external data is mapped into your AI workflows
The Cognita (RAG Framework) MCP Server exposes 7 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Cognita (RAG Framework) to Vercel AI SDK via MCP
Follow these steps to integrate the Cognita (RAG Framework) MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 7 tools from Cognita (RAG Framework) and passes them to the LLM
Why Use Vercel AI SDK with the Cognita (RAG Framework) MCP Server
Vercel AI SDK provides unique advantages when paired with Cognita (RAG Framework) through the Model Context Protocol.
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 Cognita (RAG Framework) integration everywhere
Built-in streaming UI primitives let you display Cognita (RAG Framework) tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Cognita (RAG Framework) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Cognita (RAG Framework) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Cognita (RAG Framework) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Cognita (RAG Framework) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Cognita (RAG Framework) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Cognita (RAG Framework) through natural language queries
Cognita (RAG Framework) MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect Cognita (RAG Framework) to Vercel AI SDK via MCP:
get_collection
Retrieve explicit Cloud logging tracing explicit Payload IDs
ingest_data
Provision a highly-available JSON Payload generating new Resource directories
list_collections
Identify bounded routing spaces inside the Headless Cognita RAG limit
list_data_sources
Perform structural extraction of properties driving active Buckets
list_models
Inspect deep internal arrays mitigating specific Picture constraints
rag_query
Identify precise active arrays spanning rented Transformation vectors
search_chunks
Enumerate explicitly attached structured rules exporting active Presets
Example Prompts for Cognita (RAG Framework) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Cognita (RAG Framework) immediately.
"List all RAG collections in Cognita"
"Query collection 'technical-docs' for: 'How do I configure OAuth in our API?'"
"Ingest data from source 'gh-repo-vinkius' into collection 'technical-docs'"
Troubleshooting Cognita (RAG Framework) MCP Server with Vercel AI SDK
Common issues when connecting Cognita (RAG Framework) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpCognita (RAG Framework) + Vercel AI SDK FAQ
Common questions about integrating Cognita (RAG Framework) MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
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?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Cognita (RAG Framework) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Cognita (RAG Framework) to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.