Databricks MCP server

Connect Databricks to Claude, ChatGPT, Cursor, Claude Code, Codex, Gemini, GitHub Copilot and any other MCP client, for your whole team. Metorial adds security, governance, and tracing, and gives everyone one Magic MCP URL to connect.

What you can do with the Databricks MCP server

Ask your agent in plain language. Each of these maps to a real tool on the server.

  • Use the execute sql tool in Databricks
  • Use the list mlflow experiments tool in Databricks
  • Use the manage secrets tool in Databricks
  • Use the list pipelines tool in Databricks
  • Use the get job run tool in Databricks
  • Use the manage job tool in Databricks

Supported Tools

execute_sql

Execute SQL

Execute a SQL statement on a SQL warehouse and return the results. Supports catalog and schema context, and can wait for completion or return a statement ID for asynchronous polling.

list_experiments

List MLflow Experiments

List MLflow experiments in the workspace. Experiments are containers for organizing ML runs.

manage_secrets

Manage Secrets

Manage secret scopes and secrets. Create/delete scopes, put/delete secrets, or list scopes and secret keys. Secret values cannot be read back — only metadata is returned.

list_pipelines

List Pipelines

List Delta Live Tables pipelines in the workspace. Optionally filter by name or other criteria.

get_job_run

Get Job Run

Retrieve details and status of a specific job run, including task states, timing, and output. Can also list recent runs for a given job.

manage_job

Manage Job

Create, update, or delete a multi-task workflow job. Supports notebook, Python, and SQL task types with dependencies, scheduling, and notification settings.

browse_workspace

Browse Workspace

List notebooks, folders, and other objects in a workspace directory. Can also get the status (metadata) of a specific workspace object.

list_warehouses

List SQL Warehouses

List all SQL warehouses in the workspace with their status and configuration.

manage_warehouse

Manage SQL Warehouse

Create, start, stop, or delete a SQL warehouse. SQL warehouses are compute resources for running SQL queries in Databricks SQL.

browse_catalog

Browse Unity Catalog

Navigate the Unity Catalog hierarchy: list catalogs, schemas within a catalog, tables within a schema, or get details of a specific table. Provides governance metadata including owners, comments, and data types.

manage_pipeline

Manage Pipeline

Create, start, stop, or delete Delta Live Tables pipelines. Pipelines define declarative data transformations as directed acyclic graphs.

search_runs

Search MLflow Runs

Search for MLflow runs across one or more experiments. Filter by metrics, parameters, and tags using the MLflow search syntax. Returns run metadata, metrics, and parameters.

manage_cluster

Manage Cluster

Create, edit, start, restart, stop, or permanently delete an Apache Spark cluster. To **create** a new cluster, omit `clusterId` and provide `clusterName`, `sparkVersion`, and `nodeTypeId`. To **edit** an existing cluster, provide `clusterId` along with the fields to update. To **start/restart/stop/delete**, provide `clusterId` and the corresponding `action`.

manage_dbfs

Manage DBFS

Interact with the Databricks File System (DBFS). List, read, upload, create directories, and delete files or folders.

list_jobs

List Jobs

List jobs defined in the workspace. Optionally filter by name and expand task details.

manage_notebook

Manage Notebook

Import, export, or delete notebooks and create workspace directories. Use **import** to upload notebook content (base64-encoded). Use **export** to download a notebook as a Slate attachment. Use **delete** to remove a notebook or folder.

query_serving_endpoint

Query Serving Endpoint

Send an inference request to a model serving endpoint. Works with both custom ML models and Foundation Model APIs. The request format follows OpenAI-compatible chat/completions or generic model input schemas.

run_job

Run Job

Trigger an immediate run of an existing job, optionally with override parameters. Also supports cancelling a running job run.

list_clusters

List Clusters

List all available Apache Spark clusters in the workspace. Returns cluster details including state, configuration, and scaling settings.

list_serving_endpoints

List Serving Endpoints

List all model serving endpoints in the workspace. Serving endpoints host ML models and foundation models as REST APIs.

manage_files

Manage Files

Manage files and directories with the current Databricks Files API for workspace files and Unity Catalog Volumes. Supports listing directories, creating and deleting directories, uploading files, downloading files as Slate attachments, and deleting files.

Connect Databricks to your AI client

Every client uses the same Magic MCP URL, and so does any other MCP client. Add it once and sign in with SSO.

  1. Enable Databricks in Metorial. In your Metorial portal, enable the Databricks MCP server and sign in with the account that owns the data. Access stays governed by your team policies.
  2. Add a custom connector. Open Customize, then Connectors. Select Add, then Custom, then Web.
  3. Paste your Metorial MCP URL. Name it Metorial, paste your Magic MCP URL (<your-magic-mcp-url>) and continue.
  4. Sign in. Select Add and sign in to load Databricks tools.

Run Databricks through the Metorial gateway

One governed layer for every app your agents reach, not a separate connector per tool.

  • Give Databricks and every other app to your whole team through one MCP gateway, behind your SSO.
  • Scope which teams and agents can use Databricks tools with role-based access control, and trace every call.
  • Prefer to run it yourself? Metorial is open source and self-hostable.

More integrations teams use with Databricks

Google Sheets

Create, read, and update spreadsheets and their cell data. Read and write values to individual cells, ranges, or multiple ranges using A1 notation or named ranges. Apply cell formatting including text styles, backgrounds, borders, number formats, and conditional formatting. Manage sheets (tabs) within a spreadsheet—add, delete, copy, rename, and reorder them. Create and manage embedded charts, pivot tables, filter views, data validation rules, protected ranges, named ranges, and merged cells. Perform batch operations to apply multiple updates atomically.

GitHub

Manage repositories, issues, and pull requests. Create and configure branches, star repositories, review code, and merge changes. Automate CI/CD workflows with GitHub Actions, manage workflow runs, secrets, and artifacts. Track issues with labels, milestones, and assignees. Search across code, repositories, issues, and users. Manage organizations, teams, and memberships. Create and manage projects, gists, packages, deployments, and environments. Access security alerts including code scanning, secret scanning, and Dependabot alerts. Read and write file contents in repositories. Manage webhooks, notifications, and codespaces.

Salesforce

Manage CRM data including Accounts, Contacts, Leads, Opportunities, Cases, and custom objects. Create, read, update, and delete records. Query data using SOQL and search across objects using SOSL. Perform bulk data operations for large-scale imports, exports, and migrations. Execute composite requests to batch multiple operations in a single API call. Access analytics, reports, and dashboards. Manage files and attachments associated with records. Interact with Chatter feeds, posts, and groups for social collaboration. Manage org metadata including custom objects, fields, layouts, and workflows. Query data using GraphQL for precise data retrieval across related objects.

Sharepoint

Manage SharePoint sites, document libraries, lists, and files. Create, read, update, and delete lists and list items with custom columns. Resolve site users to numeric Person/Group LookupId values. Upload, download, move, copy, and version files in document libraries. Search across sites, files, folders, lists, and list items using Microsoft Search. Manage permissions at site, list, and item levels with granular access control. Define and manage content types and site columns. Retrieve site properties and search for sites across Microsoft 365.

Airtable

Create, read, update, and delete records in Airtable bases and tables. Manage base schemas including creating tables and fields. Filter records using formulas, sort by fields, and scope queries to specific views. Upsert records to find, create, or update in a single call. Upload attachments to records, read and write record comments, list accessible bases, and receive real-time base change events through webhooks.

Google Drive

Upload, download, create, copy, move, rename, trash, and permanently delete files and folders in Google Drive. Search for files using complex queries filtering by name, MIME type, owner, modification date, labels, and other metadata. Share files and folders with specific users, groups, or domains with role-based permissions (owner, writer, commenter, reader). Manage shared drives and their members. Export Google Workspace files (Docs, Sheets, Slides) to standard formats like PDF, DOCX, and XLSX. Track file revision history and restore earlier versions. Create, read, update, and delete threaded comments and replies on files. Read label definitions and search files by label. Browse the Drive apps installed for your account. Store app-specific data in a hidden per-user folder.

Technical notes for Databricks

Manage Databricks workspaces, clusters, jobs, and data assets. Create, start, stop, and configure Apache Spark clusters. Orchestrate multi-task workflows and data pipelines with scheduled or triggered jobs. Execute SQL statements on SQL warehouses. Manage Unity Catalog resources including catalogs, schemas, tables, and volumes for data governance. Track ML experiments, manage model registry, and deploy model serving endpoints. Create and manage vector search indexes. Import, export, and organize notebooks and workspace files. Upload and download files via DBFS and Unity Catalog Volumes. Manage users, groups, service principals, and permissions. Create and publish Lakeview dashboards. Share data across organizations with Delta Sharing. Store and manage secrets for secure credential access. Receive webhook notifications for model registry events and job lifecycle events.

Frequently asked questions

Common questions about connecting Databricks to AI agents with Metorial.

  1. How many tools does the Databricks MCP server have?
    The Databricks MCP server exposes 22 tools, including Execute SQL, List MLflow Experiments, Manage Secrets. Each one is governed and traced through Metorial.
  2. Databricks exposes tools your agents call on demand; it does not publish event triggers yet. Everything still runs through one governed MCP URL.
  3. Any MCP client, including VS Code, Windsurf, Zed, OpenCode and Grok. Each one reaches the Databricks MCP server through the same Metorial URL.
  4. Use role-based access control to decide which teams, users, and agents can use Databricks and which of its tools they can call.
  5. Yes. Metorial is open source, so you can run the Databricks MCP server yourself or use the hosted gateway.

Connect Databricks to production AI agents

See how Metorial gives your team governed access to Databricks, with tracing and security controls built in.