Databricks
Databricks MCP Server provides tools for interacting with Databricks APIs through a standardized protocol, enabling AI assistants to manage clusters, jobs, notebooks, DBFS files, and execute SQL queries. Built with Python using the FastMCP framework, it authenticates with Databricks tokens and exposes functionality through well-documented tools that handle proper error reporting and response formatting. The server can be run via command line or integrated into applications, making it particularly valuable for data scientists and engineers who need to automate Databricks workspace management, monitor resources, or execute data operations without leaving their AI assistant interface.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/markov-kernel/databricks-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Databricks from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.