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.
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
28 PyPI
8
MIT
Why this server?
Enables writing Parquet files to object storage that Databricks/Spark can load or query, supporting analytics and warehouse pipelines.
Move data between Kafka, NATS, RabbitMQ, MQTT, IBM MQ, SQL databases, MongoDB, files and HTTP: publish messages and run copy routes with endpoints given inline as JSON, while the rows never pass through the model's context.
9
11
25
Apache 2.0
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
7 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.
30
172 PyPI
2
Apache 2.0
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 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
158 PyPI
1
GPL 3.0
Why this server?
Enables dbprint to connect to and profile Databricks databases, capturing table DDL, joins, and per-column statistics for offline agent context.
Gives an AI agent a database's tables, columns, value lists, null shares and joins from a dbprint snapshot committed to your repo, with no database connection or credentials. Tools list and search tables and columns, render prompt-ready context for a table, resolve a filter value to its stored spelling, and report what changed since the last snapshot.
7
222 PyPI
2
Apache 2.0
Why this server?
Allows querying Databricks via Unity Catalog or Hive metastore.
Query SQL databases (SQLite, PostgreSQL, BigQuery, Databricks) in natural language through a business semantic layer — glossary, metrics, and a data dictionary grounded against your real schema. Read-only by default, with an embedded SQLite + sqlite-vec metadata store and no external infra required.
