官方说明10 个来源MCP 服务8 天前
JordiNei/mcp-databricks-server
🐍 ☁️ - Run SQL queries, list jobs and get job status via the Databricks API
在 GitHub 查看 ↗直链 · 无中转页
配置模板（请按你的客户端调整）
claude mcp add mcp-databricks-server -- npx -y mcp-databricks-server
这是根据仓库名生成的可粘贴骨架，命令行参数与包名请以该项目 README 为准。
- ★ 数取值
- 50 ★ · JordiNeil/mcp-databricks-server · 取自 GitHub 搜索 API · （2026-10-16 20:00:20 核对）
- 来源明细
- 收录自 punkpeye/awesome-mcp-servers 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 50 ★ · 10 个来源 · mcp
常见问题（答案都来自我们的记录）
怎么安装？
我们【没有】从该仓库取到安装命令（我们的 install 覆盖率只有约 4%）。请看它的 README 或 releases 页。
它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
仓库
JordiNeil/mcp-databricks-server；我们收录于 2026-10-09；最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。第三方质量标记
Databricks MCP Server
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
A Model Context Protocol (MCP) server that connects to Databricks API, allowing LLMs to run SQL queries, list jobs, and get job status.
Features
- Run SQL queries on Databricks SQL warehouses
- List all Databricks jobs
- Get status of specific Databricks jobs
- Get detailed information about Databricks jobs
Prerequisites
- Python 3.7+
- Databricks workspace with:
- Personal access token
- SQL warehouse endpoint
- Permissions to run queries and access jobs
Setup
1. Clone this repository
2. Create and activate a virtual environment (recommended):
3. Install dependencies:
4. Create a .env file in the root directory with the following variables:
5. Test your connection (optional but recommended):
Obtaining Databricks Credentials
1. **Host**: Your Databricks instance URL (e.g., your-instance.cloud.databricks.com)
2. **Token**: Create a personal access token in Databricks:
- Go to User Settings (click your username in the top right)
- Select "Developer" tab
- Click "Manage" under "Access tokens"
- Generate a new token, and save it immediately
3. **HTTP Path**: For your SQL warehouse:
- Go to SQL Warehouses in Databricks
- Select your warehouse
- Find the connection details and copy the HTTP Path
Running the Server
Start the MCP server:
You can test the MCP server using the inspector by running
Available MCP Tools
The following MCP tools are available:
1. **run_sql_query(sql: str)** - Execute SQL queries on your Databricks SQL warehouse
2. **list_jobs()** - List all Databricks jobs in your workspace
3. **get_job_status(job_id: int)** - Get the status of a specific Databricks job by ID
4. **get_job_details(job_id: int)** - Get detailed information about a specific Databricks job
Example Usage with LLMs
When used with LLMs that support the MCP protocol, this server enables natural language interaction with your Databricks environment:
- "Show me all tables in the database"
- "Run a query to count records in the customer table"
- "List all my Databricks jobs"
- "Check the status of job #123"
- "Show me details about job #456"
Troubleshooting
Connection Issues
- Ensure your Databricks host is correct and doesn't include https:// prefix
- Check that your SQL warehouse is running and accessible
Features
- Run SQL queries on Databricks SQL warehouses
- List all Databricks jobs
- Get status of specific Databricks jobs
- Get detailed information about Databricks jobs
Prerequisites
- Python 3.7+
- Databricks workspace with:
- Personal access token
- SQL warehouse endpoint
- Permissions to run queries and access jobs
Setup
1. Clone this repository
2. Create and activate a virtual environment (recommended):
3. Install dependencies:
4. Create a .env file in the root directory with the following variables:
5. Test your connection (optional but recommended):
Obtaining Databricks Credentials
1. **Host**: Your Databricks instance URL (e.g., your-instance.cloud.databricks.com)
2. **Token**: Create a personal access token in Databricks:
- Go to User Settings (click your username in the top right)
- Select "Developer" tab
- Click "Manage" under "Access tokens"
- Generate a new token, and save it immediately
3. **HTTP Path**: For your SQL warehouse:
- Go to SQL Warehouses in Databricks
- Select your warehouse
- Find the connection details and copy the HTTP Path
Running the Server
Start the MCP server:
You can test the MCP server using the inspector by running
Available MCP Tools
The following MCP tools are available:
1. **run_sql_query(sql: str)** - Execute SQL queries on your Databricks SQL warehouse
2. **list_jobs()** - List all Databricks jobs in your workspace
3. **get_job_status(job_id: int)** - Get the status of a specific Databricks job by ID
4. **get_job_details(job_id: int)** - Get detailed information about a specific Databricks job
Example Usage with LLMs
When used with LLMs that support the MCP protocol, this server enables natural language interaction with your Databricks environment:
- "Show me all tables in the database"
- "Run a query to count records in the customer table"
- "List all my Databricks jobs"
- "Check the status of job #123"
- "Show me details about job #456"
Troubleshooting
Connection Issues
- Ensure your Databricks host is correct and doesn't include https:// prefix
- Check that your SQL warehouse is running and accessible
- 来源
- awesome · https://github.com/JordiNeil/mcp-databricks-server
- 按领域浏览
- MCP 服务
- Traction
- 50 ★
- 收录于
- 昨天
更多MCP 服务
所属领域与标签
每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。