# Databricks MCP Server

> Use this tool when you need to programmatically manage Databricks workspaces, automate cluster and job operations, or enforce data governance and security controls. It provides a comprehensive interface for interacting with Databricks resources, accepting inputs such as API calls and configuration settings, and producing outputs like managed clusters, executed jobs, and usage analytics. Ideal for use cases requiring automated DevOps, data engineering, and FinOps workflows in Databricks environments.

Canonical page: https://skillsregistry.net/skills/nainikayakkali-claud-databricks-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/nainikayakkali-claud-databricks-mcp-server

## Description

Enables AI assistants to interact with Databricks workspaces programmatically, providing comprehensive tools for cluster management, notebook operations, job orchestration, Unity Catalog data governance, user management, permissions control, and FinOps cost analytics.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** data-analytics
- **Updated:** 2026-04-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/feckqm88x3)
- **Repository:** <https://github.com/nainikayakkali/claud-databricks-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "nainikayakkali-claud-databricks-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nainikayakkali-claud-databricks-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nainikayakkali-claud-databricks-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt