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Alkemi MCP Server

@alkemi-ai

代码仓库

基本信息

分类

数据库

传输方式

stdio

作者

alkemi-ai

提交者

Matt Ferrante

关于 Alkemi MCP Server

Integrate your Alkemi Data, connected to Snowflake, Google BigQuery, DataBricks and other sources, with your MCP Client.

#database#bigquery#snowflake#databricks#big-data

Alkemi MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "alkemi": {
      "command": "npx",
      "args": [
        "@alkemiai/alkemi-mcp"
      ],
      "env": {
        "BEARER_TOKEN": "<YOUR_TOKEN>"
      }
    }
  }
}

Alkemi MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Alkemi Mcp?

Alkemi Mcp is a STDIO wrapper for the Streamable HTTP MCP endpoint at https://api.alkemi.cloud/mcp that integrates Alkemi Data—connected to Snowflake, Google BigQuery, DataBricks and other sources—with any MCP Client. It uses Alkemi to store database metadata, generate proper queries, and query the database so teams can share consistent data-access capabilities. Get a free API key at datalab.alkemi.ai.

How to use Alkemi Mcp?

Install via npx @alkemiai/alkemi-mcp or build locally from the cloned repository. Add a configuration entry to your Claude Desktop claude_desktop_config.json, setting the required BEARER_TOKEN environment variable. Optionally set MCP_NAME to name the server or PRODUCT_ID to limit scope to a single product. Multiple Alkemi Mcp instances can be configured with different names and product IDs.

Key features of Alkemi Mcp

  • STDIO wrapper for the Streamable HTTP MCP endpoint
  • Stores database metadata for accurate query generation
  • Generates proper SQL queries automatically
  • Queries the underlying database on your behalf
  • Supports multiple database sources (Snowflake, BigQuery, DataBricks, etc.)
  • Allows sharing a single MCP Server across teammates

Use cases of Alkemi Mcp

  • Query databases without requiring users to know table schemas or SQL details
  • Share a single MCP Server so all teammates have the same data-query quality
  • Narrow scope to a specific product or dataset using PRODUCT_ID
  • Connect an MCP client to cloud data warehouses like Snowflake and BigQuery

常见问题

1

What is Alkemi Mcp and how does it differ from directly querying a database?

Alkemi Mcp uses Alkemi to store database metadata, generate proper queries, and execute them—removing the need to maintain schema information in every agent or MCP Client. This prevents wrong answers and scales better for teams sharing data.

2

How do I get an API key for Alkemi Mcp?

Sign up for a free API key at [datalab.alkemi.ai](https://datalab.alkemi.ai?ref=alkemi-mcp).

3

What environment variables are required?

The `BEARER_TOKEN` is required. `MCP_NAME` and `PRODUCT_ID` are optional (use `MCP_NAME` when configuring multiple instances to avoid duplicate names).

4

What runtime or dependencies are needed?

Alkemi Mcp runs via Node.js. It can be executed with `npx` (no local install) or built from the repository using `npm install && npm run build`. The server communicates over stdio.

5

How does authentication work for Alkemi Mcp?

Authentication is handled by setting the `BEARER_TOKEN` environment variable, which provides the bearer token for the underlying Streamable HTTP MCP endpoint.

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