How to Use the MyScale (SQL Vector Database API) MCP in Claude Code

Q: How do I configure MyScale (SQL Vector Database API) for Claude Code?

Run claude mcp add --transport http -- in your terminal. Make sure all flags come before the server name.

Manage your vector database directly from the terminal. Let Claude Code run SQL migrations and monitor index builds headlessly.

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Connect MyScale (SQL Vector Database API) MCP to Claude Code

Create your Vinkius account to connect MyScale (SQL Vector Database API) to Claude Code and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup MyScale (SQL Vector Database API) with Claude Code

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Run vector migrations with Claude Code

Stop opening browser tabs to manage your database clusters. You can now execute structural changes straight from your terminal. Your CLI agent runs `ping_cluster` to verify the endpoint, then immediately starts provisioning resources. Need a new environment? The agent calls `create_vector_table` to spin up the schema. You get a fully functional hybrid database setup entirely through command-line prompts.

Automate index monitoring via MCP Server

Vector indices take time to build, especially on large production tables. You do not want to sit there refreshing a dashboard. The agent triggers `create_vector_index` and handles the waiting game for you. It loops `check_index_status` in the background, reading the exact state from the vector_indices table. Once the status shifts from InProgress to Built, your agent moves on to the next step in your CI/CD pipeline.

Query raw data from the command line

Debugging a bad vector recall usually means writing complex SQL by hand. Now you just ask your agent to find the anomaly. It uses `execute_sql_query` to run standard SELECT statements, automatically parsing the JSON output. If you need to test the actual similarity logic, it runs `vector_search`. The database handles the math, and your terminal prints the nearest neighbors. This MCP integration replaces your entire database GUI.

Setup guide

Set up MyScale (SQL Vector Database API) MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see myscale-sql-vector-database-api-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest MyScale (SQL Vector Database API) transactions." It will automatically discover and invoke the available MyScale (SQL Vector Database API) tools.

Terminal

claude mcp add --transport http myscale-sql-vector-database-api-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the MyScale (SQL Vector Database API) MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "myscale-sql-vector-database-api-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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Common questions about MyScale (SQL Vector Database API) MCP in Claude Code

Run `claude mcp add --transport http -- ` in your terminal. Make sure all flags come before the server name.

Yes. You can script the agent to create tables and build indices as part of your deployment pipeline. It handles the raw SQL execution natively.

The database automatically appends FORMAT JSON to SELECT queries. The agent parses this payload and only prints the specific rows or metrics you asked to see.

It was built for them. You can run the agent headlessly in a GitHub Action to verify database health or test vector search logic before merging a pull request.

The connection is direct from your terminal to the cluster. The server only processes the SQL strings, vector floats, and table metadata necessary to execute the specific commands you issue.

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