Mem AI (Knowledge Workspace) MCP Server for Vercel AI SDK 12 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Mem AI (Knowledge Workspace) through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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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 Mem AI (Knowledge Workspace), 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 Mem AI (Knowledge Workspace) MCP Server
Connect your Mem.ai workspace to any AI agent and take full control of your personal and team knowledge through natural conversation.
The Vercel AI SDK gives every Mem AI (Knowledge Workspace) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 12 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
- Knowledge Orchestration — Create new mems (notes) using Markdown directly from your agent, instantly transforming textual ideas into indexed knowledge vectors
- AI Semantic Search — Leverage dense semantic similarity to find notes across your entire workspace, identifying relevant information based on meaning rather than explicit keywords
- Deep Content Retrieval — Extract the full scalar text body and context metadata for specific mems to retrieve precise project details securely
- Collection Management — Establish thematic groupings (Collections) and attach live mems structurally to maintain organized project boundaries natively
- Quick Capture (Mem It) — Trigger rapid capture blocks for links, snippets, or raw thoughts, allowing your agent to log ideas without manual dashboard navigation
- Contextual Updates — Mutate existing mem content to keep project logs and meeting notes up-to-date while preserving historical knowledge mappings
- Resource Inventory — List all available mems or explore specific collections to understand your knowledge distribution and team documentation footprint
The Mem AI (Knowledge Workspace) MCP Server exposes 12 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 Mem AI (Knowledge Workspace) to Vercel AI SDK via MCP
Follow these steps to integrate the Mem AI (Knowledge Workspace) 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 12 tools from Mem AI (Knowledge Workspace) and passes them to the LLM
Why Use Vercel AI SDK with the Mem AI (Knowledge Workspace) MCP Server
Vercel AI SDK provides unique advantages when paired with Mem AI (Knowledge Workspace) 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 Mem AI (Knowledge Workspace) integration everywhere
Built-in streaming UI primitives let you display Mem AI (Knowledge Workspace) 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
Mem AI (Knowledge Workspace) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Mem AI (Knowledge Workspace) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Mem AI (Knowledge Workspace) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Mem AI (Knowledge Workspace) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Mem AI (Knowledge Workspace) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Mem AI (Knowledge Workspace) through natural language queries
Mem AI (Knowledge Workspace) MCP Tools for Vercel AI SDK (12)
These 12 tools become available when you connect Mem AI (Knowledge Workspace) to Vercel AI SDK via MCP:
add_mem_to_collection
Attach live Mems structurally inside explicitly mapped Collections
create_collection
Establish new logical thematic groupings mapping notes
create_mem
ai. Converts plain textual knowledge to indexed vectors immediately mapped implicitly via AI. Create a new mem (note) in Mem.ai using Markdown
delete_mem
No recovery is possible via API. Irreversibly vaporize a mem document globally
get_collection
Inspect specific Collection metadata elements
get_mem
Retrieve explicit full context metadata by target Mem ID
list_collection_mems
Query ALL explicit Mem bodies inside specific Collections
list_collections
Query explicitly tracked thematic Collections arrays
list_mems
Returns identifiers and raw bodies. Careful, this returns heavy payloads. List all raw mems across the global workspace
mem_it
Quick capture shortcut generating automated blocks
search_mems
AI semantic search looking into all indexed knowledge
update_mem
Replaces absolute text values so ensure `get_mem` was run to append rather than destroy inadvertently. Update pre-existing mem content natively swapping strings
Example Prompts for Mem AI (Knowledge Workspace) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Mem AI (Knowledge Workspace) immediately.
"Search my mems for anything related to 'quarterly business review'"
"Create a new mem with today's standup notes in Markdown"
"List all my thematic collections in Mem"
Troubleshooting Mem AI (Knowledge Workspace) MCP Server with Vercel AI SDK
Common issues when connecting Mem AI (Knowledge Workspace) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpMem AI (Knowledge Workspace) + Vercel AI SDK FAQ
Common questions about integrating Mem AI (Knowledge Workspace) 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 Mem AI (Knowledge Workspace) 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 Mem AI (Knowledge Workspace) to Vercel AI SDK
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.