Cognee MCP Server for Vercel AI SDK 4 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Cognee through 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 Cognee, 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 Cognee MCP Server
Connect your AI agent to Cognee — the open-source knowledge graph platform that transforms unstructured data into structured, searchable knowledge.
The Vercel AI SDK gives every Cognee tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 4 tools through 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
- Add Data — Ingest raw text, documents, or structured data into named datasets. Cognee processes and stores the data for subsequent graph construction
- Cognify — Transform ingested data into a structured knowledge graph by automatically extracting entities, relationships, and semantic connections
- Search Knowledge — Query the knowledge graph using four retrieval strategies: graph-aware completion (LLM + graph traversal), summaries, structured insights, or raw vector similarity
- Get Insights — Retrieve structured entity relationships showing how concepts connect across your knowledge base
Why Cognee over standard RAG?
- Relationship-aware — understands HOW facts connect, not just what they say
- Graph + Vector hybrid — combines graph traversal with semantic search for superior recall
- Temporal awareness — tracks when facts were added and reason over time-based connections
The Cognee MCP Server exposes 4 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 Cognee to Vercel AI SDK via MCP
Follow these steps to integrate the Cognee 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 4 tools from Cognee and passes them to the LLM
Why Use Vercel AI SDK with the Cognee MCP Server
Vercel AI SDK provides unique advantages when paired with Cognee 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 Cognee integration everywhere
Built-in streaming UI primitives let you display Cognee 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
Cognee + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Cognee MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Cognee in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Cognee tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Cognee capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Cognee through natural language queries
Cognee MCP Tools for Vercel AI SDK (4)
These 4 tools become available when you connect Cognee to Vercel AI SDK via MCP:
cognee_add_data
After ingestion, use the cognify tool to process the data into a structured knowledge graph with entities and relationships. Ingest text or documents into the Cognee knowledge base. This is the first step before building a knowledge graph
cognee_cognify
This step extracts entities, identifies relationships, generates embeddings, and creates the graph structure needed for intelligent search. Process ingested data into a structured knowledge graph. Extracts entities, relationships, and builds a searchable graph structure
cognee_get_insights
Useful for understanding relationships between topics, discovering hidden connections, and building comprehensive knowledge views. Retrieve structured entity relationships and insights from the knowledge graph
cognee_search
Search the knowledge graph using natural language. Returns context-aware answers using graph traversal and semantic search
Example Prompts for Cognee in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Cognee immediately.
"Add this research data to my knowledge base: 'Transformer models were introduced by Vaswani et al. in 2017 in the paper Attention Is All You Need. They use self-attention mechanisms and have become the foundation for models like GPT, BERT, and T5.'"
"Process my data into a knowledge graph."
"What is the relationship between Transformers and GPT?"
Troubleshooting Cognee MCP Server with Vercel AI SDK
Common issues when connecting Cognee to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpCognee + Vercel AI SDK FAQ
Common questions about integrating Cognee 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 Cognee 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 Cognee to Vercel AI SDK
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.