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mlflow-mcp-server

get-best-run

Read-only

Find the run achieving the optimal metric value in your MLflow experiment. Specify the metric and whether to maximize or minimize.

Instructions

Find the run with the best (max/min) value of a metric in an experiment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdNoExperiment ID (defaults to MLFLOW_EXPERIMENT_ID)
metricYesMetric key to optimize on (e.g. 'accuracy', 'loss')
ascendingNoTrue to minimize (e.g. loss); default maximizes
filterNoAdditional filter on top of metric ordering
Behavior3/5

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

Annotations already indicate read-only and open-world, so description adds value by explaining metric optimization. However, it does not disclose tie-breaking behavior or handling of missing runs.

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

Conciseness5/5

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

Single sentence, no unnecessary words, directly states functionality.

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?

Lacks specification of return value structure (no output schema), which could help agents understand data shape. For a simple tool, it is adequate but not fully complete.

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

Parameters3/5

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

All parameters have schema descriptions (100% coverage), so description adds little beyond stating the goal. The description reinforces max/min but does not provide additional parameter context.

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

Purpose5/5

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

Description clearly states verb 'find', resource 'run', and qualifier 'best (max/min) value of a metric'. It distinguishes from siblings like 'get-run' (specific run) and 'search-runs' (list) by focusing on optimization.

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

Usage Guidelines4/5

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

Description implies use when you need the best run based on a metric, but lacks explicit when-not-to-use or alternatives. However, it is clear enough for the intended use case.

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

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