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Databricks Unity Catalog MCP Server

Databricks Unity Catalog MCP Server

by revodatanl

get-job-runs

Retrieve recent runs for specified Databricks job IDs, returning a configurable number per job sorted by most recent execution.

Instructions

        Get recent job runs by job id.

        Args:
            - job_ids: List of job ids for which to get the runs
            - amount: Amount of runs to get per job, sorted by most recent
        

Input Schema

NameRequiredDescriptionDefault
job_idsYes
n_recentNo

Output Schema

NameRequiredDescriptionDefault
errorYes
contentYes
successYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears the full behavioral burden. It discloses only that results are sorted by most recent, saying nothing about permissions, result ordering across multiple job ids, truncation behavior, or what a run record contains beyond what the output schema implies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The prose is short, but it is written as a Python docstring with an 'Args:' block, which spends lines restating parameter names rather than adding value, and the parameter it restates does not match the schema. Front-loading is fine, but the structure is boilerplate rather than purposeful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return shape need not be explained. However, for a two-parameter query tool with zero schema coverage and no annotations, the description leaves material gaps: the 'amount'/'n_recent' mismatch, the default of 1, and the absence of any usage context relative to the six sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it only partly does. More seriously, it refers to a parameter called 'amount' while the schema defines 'n_recent' (default 1), so an agent mapping the prose to the schema encounters a name mismatch with no reconciliation or mention of the default.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first line states a specific verb and resource: fetch recent job runs for given job ids. It is distinguishable from get-job-details (which presumably returns one job's configuration) because it explicitly returns runs. It falls short of a 5 because it never names or contrasts with any sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus get-jobs or get-job-details, no mention of prerequisites, and no statement of limits on how far back 'recent' reaches. The agent must infer usage entirely from the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.