Databricks Genie MCP

Communauté Données et bases de données

Databricks Genie API: ask natural language questions, run SQL queries and interact with Databricks conversational agents.

Que pouvez-vous faire avec Databricks Genie MCP ?

  • List Genie spaces available in your Databricks workspace (Currently Manual/Using Resource)
  • Fetch metadata (title, description) of a specific Genie space
  • Start new Genie conversations with natural language questions
  • Ask follow-up questions in ongoing Genie conversations
  • Retrieve SQL and result tables in structured format

Installation

Les étapes d'installation sont dans la documentation ci-dessous. Documentation

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Databricks Genie MCP Server
  2. ✨ Features
  3. 🧱 Prerequisites
  4. ⚙️ Setup
  5. 🧪 Test the Server
  6. 💬 Use with Claude Desktop
  7. 🧾 Obtaining Databricks Credentials
  8. 🚀 Running the Server
  9. 🧰 Available MCP Tools
  10. 🛠️ Troubleshooting
  11. 🔐 Security Considerations
  12. Claude Desktop Screenshots

Databricks Genie MCP Server

A Model Context Protocol (MCP) server that connects to the Databricks Genie API, allowing LLMs to ask natural language questions, run SQL queries, and interact with Databricks conversational agents.

✨ Features

  • List Genie spaces available in your Databricks workspace (Currently Manual/Using Resource)
  • Fetch metadata (title, description) of a specific Genie space
  • Start new Genie conversations with natural language questions
  • Ask follow-up questions in ongoing Genie conversations
  • Retrieve SQL and result tables in structured format

🧱 Prerequisites

  • Python 3.7+
  • Databricks workspace with:
    • Personal access token
    • Genie API enabled
    • Permissions to access Genie spaces and run queries

⚙️ Setup

  1. Clone this repository
  2. Create and activate a virtual environment (recommended):
 python -m venv .venv
 source .venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Create a .env file in the root directory with the following variables:

DATABRICKS_HOST=your-databricks-instance.cloud.databricks.com # Don't add https
DATABRICKS_TOKEN=your-personal-access-token

📌 Manually Adding Genie Space IDs

Note:
At this time, the Databricks Genie API does not provide a public endpoint to list all available space IDs and titles. (afaik) As a workaround, you need to manually add the Genie space IDs and their titles in the get_genie_space_id() function in main.py.

🧪 Test the Server

You can test the MCP server using the inspector (optional but recommended):

npx @modelcontextprotocol/inspector python main.py

OR

You can directly build and run docker to test the server

💬 Use with Claude Desktop

Download Claude Desktop

Install Your MCP Server: From your project directory, run:

mcp install main.py

Once Server Installed

  1. Connect in Claude
  2. Open Claude Desktop
  3. Click Resources → Add Resource
  4. Select your Genie MCP Server
  5. Start chatting with your data using natural language! 🎯

🧾 Obtaining Databricks Credentials

Host Your Databricks instance URL (e.g., your-instance.cloud.databricks.com) — do not include https://

Token

  1. Go to your Databricks workspace
  2. Click your username (top right) → User Settings
  3. Under the Developer tab, click Manage under "Access tokens"
  4. Generate a new token and copy it

🚀 Running the Server

python main.py

This will start the Genie MCP server over the stdio transport for LLM interaction.

🧰 Available MCP Tools

The following MCP tools are available:

Tool Description

  1. get_genie_space_id() List available Genie space IDs and titles
  2. get_space_info(space_id: str) Retrieve title and description of a Genie space
  3. ask_genie(space_id: str, question: str) Start a new Genie conversation and get results
  4. follow_up(space_id: str, conversation_id: str, question: str) Continue an existing Genie conversation

🛠️ Troubleshooting

Common Issues

  • Invalid host: Ensure the host does not include https://
  • Token error: Make sure your personal access token is valid and has access to Genie
  • Timeout: Check if the Genie space is accessible and not idle/expired
  • No data returned: Ensure your query is valid for the selected space

🔐 Security Considerations

  • Keep your .env file secure and never commit it to version control
  • Use minimal scope tokens with expiration whenever possible
  • Avoid exposing this server in public-facing environments unless authenticated

Claude Desktop Screenshots

Questions fréquentes

Qu'est-ce que Databricks Genie MCP ?

Databricks Genie API: ask natural language questions, run SQL queries and interact with Databricks conversational agents.

Comment installer Databricks Genie MCP ?

Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.

Databricks Genie MCP est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Databricks Genie MCP ?

Il est publié par yashshingvi. AI.tn le référence sans le maintenir ni le recommander.

Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.