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.
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
6 npm
MIT
Why this server?
Enables Semantic Rails to connect to Databricks as a warehouse target for running and validating semantic layer queries against Databricks data.
Enables agents to interact with a governed semantic layer for querying and authoring metrics, providing tools for discovery, planning, validation, and execution of analytics queries.
16
Apache 2.0
Why this server?
Provides detection and redaction of sensitive data in Databricks notebooks and data before it reaches an AI agent.
Detect and redact PII, PHI, PCI and secrets — SSNs, credit cards, passports, API keys and cloud credentials — in text and in local files, using the Strac DLP API. Five tools: redact_text, detect_sensitive_data, detect_file, redact_file and detokenize.
5
7
MIT
Why this server?
Manages tag-based data masking, access governance, and classification for Databricks databases through the ALTR platform.
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?
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 interact with over 50 SQL and NoSQL databases through MCP tools for querying, schema inspection, and table management.
5
1
MIT
Why this server?
Provides access to Databricks functionality through tools that allow interacting with clusters (listing, creating, terminating, starting), jobs (listing, running), notebooks (listing, exporting), files (browsing DBFS paths), and executing SQL queries on a Databricks instance.
A server that implements the Model Completion Protocol (MCP) to allow LLMs to interact with Databricks resources including clusters, jobs, notebooks, and SQL execution through natural language.
11
49
MIT
Why this server?
Provides tools for managing Databricks datamart definitions within TROCCO, including creating, updating, and running datamart jobs, as well as analyzing SQL for audit purposes.
