ClickHouse (Vector Search) 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 ClickHouse (Vector Search) 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 ClickHouse (Vector Search), 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 ClickHouse (Vector Search) MCP Server
Connect your ClickHouse cluster to any AI agent and take full control of your analytical and vector data through natural conversation.
The Vercel AI SDK gives every ClickHouse (Vector Search) 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
- Schema Management — List databases and tables, and inspect deep column schemas including specialized Array(Float32) vector types
- SQL Execution — Push arbitrary DML, DDL, or SELECT queries to your cluster to manage data and generate real-time reports
- Vector Search — Identify mathematical distance traces using cosineDistance or L2Distance metrics for high-dimensional semantic search
- Cluster Monitoring — Extract internal structural states, row counts, and compression ratios to audit cluster health
- Capability Auditing — Check instance versions and binary limits to identify exact capability branches like HNSW support
The ClickHouse (Vector Search) 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 ClickHouse (Vector Search) to Vercel AI SDK via MCP
Follow these steps to integrate the ClickHouse (Vector Search) 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 ClickHouse (Vector Search) and passes them to the LLM
Why Use Vercel AI SDK with the ClickHouse (Vector Search) MCP Server
Vercel AI SDK provides unique advantages when paired with ClickHouse (Vector Search) 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 ClickHouse (Vector Search) integration everywhere
Built-in streaming UI primitives let you display ClickHouse (Vector Search) 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
ClickHouse (Vector Search) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the ClickHouse (Vector Search) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query ClickHouse (Vector Search) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate ClickHouse (Vector Search) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed ClickHouse (Vector Search) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with ClickHouse (Vector Search) through natural language queries
ClickHouse (Vector Search) MCP Tools for Vercel AI SDK (7)
These 7 tools become available when you connect ClickHouse (Vector Search) to Vercel AI SDK via MCP:
describe_table
Perform structural extraction of properties driving active column schemas
execute_sql
Provision a highly-available SQL execution pushing arbitrary arbitrary DML/DDL or SELECTs
get_table_stats
Extracts explicitly attached internal structural states pulling cluster health
get_version
g. HNSW support). Identify precise active cluster limits spanning the execution runtime
list_databases
Identify bounded logical arrays managing top-level ClickHouse schemas
list_tables
Retrieve the exact structural matching verifying table limits inside a database
vector_search
Identify explicit mathematical distance traces routing Vector Embeddings
Example Prompts for ClickHouse (Vector Search) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with ClickHouse (Vector Search) immediately.
"List all databases in my ClickHouse cluster"
"Find the top 5 most similar records in table 'embeddings' using this vector: [0.1, 0.5, -0.2]"
"Get table stats for 'analytics_prod.sales_data'"
Troubleshooting ClickHouse (Vector Search) MCP Server with Vercel AI SDK
Common issues when connecting ClickHouse (Vector Search) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpClickHouse (Vector Search) + Vercel AI SDK FAQ
Common questions about integrating ClickHouse (Vector Search) 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 ClickHouse (Vector Search) 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 ClickHouse (Vector Search) to Vercel AI SDK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.