Databricks is a data analytics platform that provides data lakehouse solutions for businesses, combining data warehouses and data lakes to offer unified analytics for data engineering, machine learning, and business intelligence.
Enables AI assistants to manage data security on the ALTR platform for Snowflake, Databricks, and OLTP databases, offering 99 tools across 10 domains including tag masking, policies, classification, and access governance.
100
GPL 3.0
Why this server?
Enables natural language querying and analysis of Databricks SQL warehouses, returning markdown reports with tables and charts.
Celp-MCP enables natural-language analytics over SQL, MongoDB, and Databricks warehouses through MCP-compatible clients, converting questions into multi-step database plans and returning markdown reports.
4
63
MIT
Why this server?
Supports data quality checks on Databricks tables, including ML anomaly detection and auto-generated SQL remediation.
Agentic data quality MCP server — runs structured validation rules against warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres), diagnoses failures with LLM root cause analysis, and proposes SQL remediations. Full audit trail of every AI decision.
6
4
Apache 2.0
Why this server?
Detects and redacts Databricks personal access tokens in text.
Enables AI agents to scan text for leaked secrets and prompt injection markers, and redact them before reaching an LLM.
2
1
MIT
Why this server?
Allows connection to Databricks-hosted MLflow tracking servers using Databricks PAT or service-principal tokens, enabling management of experiments, runs, models, and traces on Databricks.
A Model Context Protocol server that enables LLMs to interact with MLflow tracking servers, allowing users to query experiments, analyze runs, compare metrics, manage the model registry, and promote models through natural language.
40
14
MIT
Why this server?
Captures SQL data-model metadata from Databricks via ODBC, exposing table schemas, relationships, and lineage information.
