ClickHouse (Vector Search) Connector for AI agents.
7 live capabilities
Query analytical data and perform high-speed vector searches on your cluster.
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Why people use ClickHouse (Vector Search)
ClickHouse (Vector Search) for Real-Time Analytical SQL Queries
This Connector changes that by letting your AI agent do the heavy lifting. You just ask for the data you need, and the agent handles the SQL execution and data retrieval. You get the answers you need directly in your chat window, skipping the copy-paste cycle entirely.
What Vinkius changes
You get a natural language interface for your entire ClickHouse data environment.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Finding similar products
A shopper asks for items like a specific product.
- Real-world use case 02
Quick report generation
An analyst asks for last month's sales by region.
- Real-world use case 03
Cluster health check
A DBA asks about storage efficiency.
Complete set · 7capabilities
The complete ClickHouse (Vector Search) capability set.
These are the exact actions your AI can choose when you ask it to work with ClickHouse (Vector Search).
01—04
4 capabilities in this set.
Part of 7 available through ClickHouse (Vector Search).
- 01 Capability
Execute sql
Run any DML, DDL, or SELECT query against your cluster. This lets you manage data and generate reports using only natural language.
- 02 Capability
Vector search
Identify records based on mathematical distance traces for embeddings. This makes it easy to find similar items using cosine or L2 metrics.
- 03 Capability
List databases
Show all the top-level schemas in your ClickHouse cluster. This helps you navigate your data environment quickly.
- 04 Capability
List tables
Retrieve the exact tables and limits inside a specific database. Use this to see what data is available for querying.
05—07
3 capabilities in this set.
Part of 7 available through ClickHouse (Vector Search).
- 05 Capability
Describe table
Pull the schema properties and column types for an active table. This helps you understand your data structure without manual inspection.
- 06 Capability
Get table stats
Pull internal states like row counts and compression ratios. Use this to monitor your cluster health and storage efficiency.
- 07 Capability
Get version
Identify the active cluster limits and binary support versions. This helps you verify if your instance supports specific features like HNSW.
Set up in minutes
One URL. Then ask ClickHouse (Vector Search) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use ClickHouse (Vector Search) from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it ClickHouse (Vector Search), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable ClickHouse (Vector Search) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the ClickHouse (Vector Search) URL.
- Step 03
Save and start
Save the connection and enable ClickHouse (Vector Search) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"clickhouse-vector-search": {
"url": "https://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using ClickHouse (Vector Search)
Open Agent mode in chat and ask: "Using ClickHouse (Vector Search), help me...". 7 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"clickhouse-vector-search": {
"url": "https://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using ClickHouse (Vector Search)
Ask Copilot: "Using ClickHouse (Vector Search), help me...". 7 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"clickhouse-vector-search": {
"url": "https://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using ClickHouse (Vector Search)
Open Cascade and ask: "Using ClickHouse (Vector Search), help me...". 7 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"clickhouse-vector-search": {
"url": "https://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using ClickHouse (Vector Search)
Ask Cline: "Using ClickHouse (Vector Search), help me...". 7 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add clickhouse-vector-search --transport http "https://edge.vinkius.com/vk_preview_567ij3B5hJvT6KRM8Z5LcFbGNttrwDvwD2OPp6c2/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using ClickHouse (Vector Search)
Ask Claude: "Using ClickHouse (Vector Search), show me...". 7 tools are ready
Where the request belongs
Work ClickHouse can move forward.
This is for data professionals who are tired of writing boilerplate SQL for every single request or AI engineers who need to test vector similarity without manual overhead.
Data Analyst
Uses it to generate complex reports and explore data distributions via chat.
AI Developer
Tests and debugs vector similarity searches and semantic matching.
Database Administrator
Monitors table statistics and compression ratios across different environments.
Product Manager
Verifies analytical data and vector distributions during the prototyping phase.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Oracle Vector DB
Run vector similarity searches on Oracle 23ai. execute VECTOR_DISTANCE queries, inspect schemas, list vector indexes, and query tables from any AI agent.
Couchbase (Vector & NoSQL)
Manage vector search and NoSQL via Couchbase. execute N1QL queries, perform KNN vector searches, and audit documents directly from any AI agent.
Bring your own AI
Change the model, client or framework. Keep ClickHouse connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about ClickHouse.
The practical details behind the request, access and result.
Can the ClickHouse (Vector Search) MCP run my custom SQL queries?
Yes, it can. You can ask your agent to run any DML or SELECT statements, and it will execute them on your cluster and give you the results directly.
How does ClickHouse (Vector Search) handle vector embeddings?
It uses the vector_search capability to find records based on mathematical distances like cosine or L2. This makes it easy to find similar items in your data using natural language.
Can I use ClickHouse (Vector Search) to check my database health?
You can. The Connector can pull internal stats like row counts and compression ratios, so you can ask your agent to audit your cluster's performance and storage.
Does ClickHouse (Vector Search) work with my self-hosted cluster?
Yes, it works with both ClickHouse Cloud and self-hosted instances. You just need to provide your URL, username, and password to get started.
Can I see my table schemas using ClickHouse (Vector Search)?
Yes, you can ask your agent to describe any table. It will pull the column types and properties so you know exactly how your data is structured.
Is ClickHouse (Vector Search) good for real-time analytics?
It's built for high-performance data. Because it connects to ClickHouse, your agent can perform fast queries on large datasets for real-time reporting.
Can my agent perform high-speed vector similarity searches?
Yes. Provide the database, table, and the vector embedding array in JSON format. The agent uses ClickHouse's native distance functions (cosine or L2) to return the closest matches, leveraging ClickHouse's industry-leading OLAP performance.
Can I execute arbitrary SQL commands directly through the agent?
Absolutely. The 'execute_sql' capability allows you to push any valid ClickHouse SQL (DML, DDL, or SELECT) to your cluster. This is perfect for managing tables, updating records, or generating custom analytical reports on the fly.
How do I check if my ClickHouse instance supports HNSW indices?
Ask your agent to get the version details. The agent checks your ClickHouse build and identifies exactly which capability branches are active, confirming if advanced vector features like HNSW support are available in your runtime environment.
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Give your agent a direct line to ClickHouse.
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