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This MCP server enables LLMs to interact with Databricks Genie for natural language querying and data exploration, requiring secure handling of Databricks credentials.
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This MCP server enables LLMs to interact with Databricks Genie for natural language querying and data exploration, requiring secure handling of Databricks credentials.
This server is relatively safe for read-only operations within Databricks Genie. However, the risk of token exposure and potential data leakage necessitates careful handling of credentials and input validation. Avoid using it with highly sensitive data without additional security measures.
Performance depends on the complexity of the SQL queries generated and the size of the datasets being queried. Large datasets may result in slow response times.
Cost is primarily determined by Databricks compute resources used to execute queries. Complex queries and large datasets will increase costs.
pip install -r requirements.txtDATABRICKS_HOSTDATABRICKS_TOKENget_genie_space_id()Lists available Genie space IDs and titles.
Read-only operation, no side effects.
get_space_info(space_id: str)Retrieves title and description of a Genie space.
Read-only operation, no side effects.
ask_genie(space_id: str, question: str)Starts a new Genie conversation and gets results based on a question.
Executes queries, potential for resource consumption.
follow_up(space_id: str, conversation_id: str, question: str)Continues an existing Genie conversation with a follow-up question.
Executes queries, potential for resource consumption.
Token
hybrid
This server is relatively safe for read-only operations within Databricks Genie. However, the risk of token exposure and potential data leakage necessitates careful handling of credentials and input validation. Avoid using it with highly sensitive data without additional security measures.
Autonomy is limited by the permissions of the Databricks token and the capabilities of the Genie API. Ensure the token has appropriate access and the Genie space is configured securely.
Production Tip
Monitor Databricks usage and costs to prevent unexpected expenses due to LLM-driven queries.
Store the token securely, use minimal scope tokens, and rotate tokens regularly. Avoid committing the .env file to version control.
Immediately revoke the compromised token and generate a new one. Investigate any unauthorized activity.
No, the server is configured for a single Databricks workspace specified in the .env file.
Implement error handling in your LLM application to gracefully handle API errors and provide informative messages to the user.
The limit depends on the Databricks cluster configuration and the Genie API's limitations. Large datasets may require optimized queries.
Monitor Databricks usage and costs in the Databricks console. Set up alerts to notify you of unexpected expenses.
No, the current implementation is limited to read-only operations and executing queries.