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mlflow-mcp-server

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search-runs-by-tags

Find MLflow runs whose tags match specified key/value pairs. Returns runs satisfying all given tag conditions.

Instructions

Find runs whose tags match all of the given key/value pairs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdsNoExperiment IDs (defaults to MLFLOW_EXPERIMENT_ID)
tagsYesTag key/value pairs to AND together
maxResultsNo
orderByNo
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It only states that tags are ANDed together, but omits details on pagination (maxResults), ordering (orderBy), error handling, or performance implications.

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?

The description is a single sentence with no redundant words. It efficiently conveys the core purpose without extraneous information.

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

Completeness2/5

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

Given the absence of annotations and output schema, the description fails to adequately define behavior for all 4 parameters. It does not explain default values, ordering semantics, or return format, leaving significant gaps for correct usage.

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?

Schema coverage is 50%, with descriptions for experimentIds and tags. The description adds 'AND together' for tags, clarifying boolean logic, but provides no additional meaning for maxResults, orderBy, or experimentIds beyond the schema.

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?

The description clearly states the action ('Find'), the resource ('runs'), and the filtering condition ('tags match all of the given key/value pairs'). This distinguishes it from the generic sibling 'search-runs' which likely has broader criteria.

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

Usage Guidelines3/5

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

The description implies usage for tag-based search but does not provide explicit guidance on when to use this tool versus alternatives like 'search-runs'. No exclusions or context signals are mentioned.

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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