Databricks Unity Catalog (UC) allows for detailed documentation of your data assets, including catalogs, schemas, tables, and columns. Documenting
Databricks Unity Catalog (UC) allows for detailed documentation of your data assets, including catalogs, schemas, tables, and columns. Documenting these assets
This Model Context Protocol (MCP) server is designed to interact with Databricks, with a strong focus on leveraging Unity Catalog (UC) metadata and enabling comprehensive data lineage exploration. The primary goal is to equip an AI agent with a comprehensive set of tools, enabling it to become independent in answering questions about your data. By autonomously exploring UC, understanding data structures, analyzing data lineage (including notebook and job dependencies), and executing SQL queries, the agent can fulfill data requests without direct human intervention for each step.
Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| LLM | Focused Output: All descriptive tools return information in Markdown format, optimized for consumption by Large Language Models, making it easier for agents to |
| Args | sql: The complete SQL query string to execute. |
| schema_name | The name of the schema to describe. |
| include_columns | If True, lists tables with their columns. Defaults to False for a briefer summary. |
| include_lineage | Set to True to fetch comprehensive lineage (tables, notebooks, jobs). Defaults to False. May take longer to retrieve but provides rich context for understanding |
{
"mcpServers": {
"databricks": {
"command": "uv",
"args": [
"--directory",
"/path/to/your/mcp-databricks-server",
"run",
"main.py"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
Enables AI agents to interact with Minecraft using the Model Context Protocol via Mineflayer.
Automates Unity workflows and manipulates assets using local large language models via Ollama.
Analyze chess positions and get professional evaluations using Stockfish within Claude.
Facilitates a trivia game where AI models generate content and manage gameplay through the Model Context Protocol.
Building a daily briefing for a human is mostly about sourcing the parts you can't write personally — the joke, the history snippet, the puzzle, the
Daily content for AI agents. History, chess, investing, wrongology, more. 10 channels. Free trial.