MyScale (SQL Vector Database API) Connector for AI agents.
6 live capabilities
Manage high-performance RAG backends and vector search using standard SQL commands.
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Why people use MyScale (SQL Vector Database API)
MyScale (SQL Vector Database API) for Automated RAG Indexing
With this Connector, you just tell your agent to create an HNSW or ScaNN index. It handles the syntax, initiates the build, and can even tell you when it's done. You get a finished, searchable index without ever touching the raw SQL commands.
What Vinkius changes
You get a natural language interface for high-performance vector database management.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Rapid RAG Backend Prototyping
An AI engineer needs to test a new embedding model.
- Real-world use case 02
Real-time Index Monitoring
A data scientist is deploying a large dataset and needs to know when the build is finished.
- Real-world use case 03
Complex Filtered Similarity Search
A developer needs to find items with a specific attribute and high similarity.
Complete set · 6capabilities
The complete MyScale (SQL Vector Database API) capability set.
These are the exact actions your AI can choose when you ask it to work with MyScale (SQL Vector Database API).
01—03
3 capabilities in this set.
Part of 6 available through MyScale (SQL Vector Database API).
- 01 Capability
Vector search
Perform a similarity search where the Connector handles the SQL and distance functions. You get relevant results based on vector proximity.
- 02 Capability
Create vector index
Add a new vector index to a specific table. Use this to optimize search performance for your most frequent queries.
- 03 Capability
Ping cluster
Confirm your cluster is reachable and your credentials are correct. It's a quick way to verify your connection before starting work.
04—06
3 capabilities in this set.
Part of 6 available through MyScale (SQL Vector Database API).
- 04 Capability
Create vector table
Create a new table with a dedicated vector column. This helps you set up new data structures for embeddings quickly.
- 05 Capability
Execute sql query
Run any SQL query on your cluster with automatic JSON formatting for results. It's perfect for standard data retrieval.
- 06 Capability
Check index status
See if your vector indices are built, in progress, or errored out. This keeps you informed on the progress of large index builds.
Set up in minutes
One URL. Then ask MyScale (SQL Vector Database API) to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use MyScale (SQL Vector Database API) 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_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API), and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable MyScale (SQL Vector Database API) for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API) URL.
- Step 03
Save and start
Save the connection and enable MyScale (SQL Vector Database API) in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"myscale-sql-vector-database-api": {
"url": "https://edge.vinkius.com/vk_preview_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API)
Open Agent mode in chat and ask: "Using MyScale (SQL Vector Database API), help me...". 6 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"myscale-sql-vector-database-api": {
"url": "https://edge.vinkius.com/vk_preview_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API)
Ask Copilot: "Using MyScale (SQL Vector Database API), help me...". 6 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"myscale-sql-vector-database-api": {
"url": "https://edge.vinkius.com/vk_preview_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API)
Open Cascade and ask: "Using MyScale (SQL Vector Database API), help me...". 6 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"myscale-sql-vector-database-api": {
"url": "https://edge.vinkius.com/vk_preview_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API)
Ask Cline: "Using MyScale (SQL Vector Database API), help me...". 6 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add myscale-sql-vector-database-api --transport http "https://edge.vinkius.com/vk_preview_vWeauVyztoYzGBsy6h9azMYGgJ3R8tQDDZfTvuoy/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 MyScale (SQL Vector Database API)
Ask Claude: "Using MyScale (SQL Vector Database API), show me...". 6 tools are ready
Where the request belongs
Work MyScale can move forward.
This is for the AI engineer who needs to iterate on RAG systems quickly, the data scientist monitoring large scale vector indices, and the backend developer who wants to manage SQL data without switching capabilities.
AI Engineer
Tests different vector search parameters and inspects data distributions during RAG development without leaving the chat.
Data Scientist
Monitors the health of large-scale vector indices and manages RAG backends in real time.
Backend Developer
Handles database maintenance, schema updates, and data insertion using plain English commands.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Connect your AI to Supabase Vector. Execute pgvector semantic searches, manage embeddings, and run relational database queries directly from your terminal.
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Manage vector search and NoSQL via Couchbase. execute N1QL queries, perform KNN vector searches, and audit documents directly from any AI agent.
LanceDB (Serverless Vector DB)
Manage vectorized data via LanceDB. perform similarity searches, create tables, and manage multi-modal embeddings.
Milvus (Open-Source Vector Database)
Manage vector storage via Milvus. perform ANN searches, query scalar entities, and audit collections.
Qdrant
Empower your AI to interact directly with your Qdrant vector database. query clusters, perform similarity searches, and manage collections effortlessly.
MongoDB Atlas Vector Search
Manage vector storage via MongoDB Atlas. perform similarity searches, query MQL documents, and audit collections.
Bring your own AI
Change the model, client or framework. Keep MyScale connected.
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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 MyScale.
The practical details behind the request, access and result.
How do I connect MyScale (SQL Vector Database API) MCP to my agent?
Once you subscribe, you'll just need to provide your MyScale Cluster URL, username, and password in your client settings. This connects your agent directly to your database.
Can MyScale (SQL Vector Database API) MCP handle complex SQL joins?
Yes, it can execute arbitrary SQL queries. Your agent can handle complex joins and filters just like a standard SQL database.
Does MyScale (SQL Vector Database API) MCP support HNSW indices?
It does. You can use your agent to create and monitor HNSW indices, which are excellent for high-performance similarity searches.
How does MyScale (SQL Vector Database API) MCP speed up my RAG workflow?
It lets you manage your RAG backend using natural language. You can quickly create tables, check index health, and run searches without writing manual SQL code.
Is MyScale (SQL Vector Database API) MCP compatible with ClickHouse?
Yes, it's designed to work with MyScale, which combines ClickHouse power with advanced vector search capabilities.
Can I use MyScale (SQL Vector Database API) MCP to manage multiple clusters?
You can manage your specific cluster by providing the correct URL and credentials. This allows your agent to handle the maintenance of your production vector data.
How can I check if my vector index has finished building?
Use the check_index_status capability. It queries the system tables to show you the current status (Built, InProgress, or Error) for all vector indices in your cluster.
Can I perform a vector search with metadata filtering?
Yes! The vector_search capability includes an optional filter parameter where you can provide a SQL WHERE clause (e.g., "category = 'science'") to restrict your search results.
What SQL commands are supported by the execute capability?
The execute_sql_query capability supports standard MyScale/ClickHouse SQL, including SELECT, CREATE, ALTER, and INSERT. For SELECT queries, it automatically formats the output as JSON for the agent.
One connection away
Give your agent a direct line to MyScale.
Connect MyScale once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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