Databricks Agent ToolsSAFE
Overview
From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.
Table of Contents =================
- Databricks MCP servers
- Table of Contents
- Overview
- Unity Catalog Server
- Databricks Managed MCP servers
- Overview
- Usage (locally via
stdiotransport) - Supported tools
- Deploying UC MCP server on Databricks Apps
- Using
databricks bundleCLI - Using
databricks appsCLI - Connecting to the UC MCP server deployed on Databricks Apps
- Developer Tools Server
- Deploying a custom MCP server on Databricks Apps
- Support
- Contributing
Databricks Managed MCP servers
Databricks provides ready-to-use MCP servers that let agents query data and access tools in Unity Catalog. Permissions are always enforced, so agents and users can only access the tools and data they’re allowed to. For more info see the Databricks docs AWS|Azure|GCP.
Overview
An experimental collection of MCP servers to help AI agents fetch enterprise data from Databricks, automate common developer actions on Databricks, etc:
- 
5 read · 4 write · 0 destructive.
| Tool | Risk | Description |
|---|---|---|
add | write | Add two numbers |
genie_create_message | write | Create a message in a conversation. |
genie_execute_query | write | Execute SQL query from a message attachment. |
genie_generate_download | read | Generate download link for full query result. |
genie_get_message | read | Get a message from a conversation. |
genie_get_query_result | read | Get SQL query result from a message attachment. |
genie_get_space | read | Get details of a Genie space. |
genie_poll_until_complete | read | Poll a message until its status is COMPLETED or timeout. |
genie_start_conversation | write | Start a new conversation in a Genie space. |
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- declared (1 observation(s))
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- not all pinned
- Secrets in source
- none-found
Findings (1)
uv
Gates applied: no_behavioural_pass.
7a86423c055afull audit observations/trust-audit/mcp-server/databrickslabs__databricks-agent-tools.json · Report an issue / request a re-scanAudit history
Every audit this server has had. A grade with a past is a grade somebody is still checking.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-07 | 7a86423c055a | SAFE | B | 89 | first audit |
Questions
What tools does Databricks Agent Tools expose?
9 in total: 5 read-only, 4 that write, and 0 that can delete or overwrite. Every one is listed on this page with its risk.
Is Databricks Agent Tools safe to connect to an agent?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean server reads B.
What credentials does Databricks Agent Tools need?
No credential environment variables were found in its source, so it appears to need none.
How does Databricks Agent Tools run?
It speaks stdio and streamable-http, so it runs as a local process your client starts. It is published on PyPI as databricks-labs-mcp.
How current is this page?
The grade is for one exact copy of the source (7a86423c055a), read on 2026-10-07. The repository is watched and re-audited when it changes.