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mlflow-mcp-server

by us-all

search-runs

Filter and search MLflow runs by experiment IDs, metrics, and parameters. Paginate results using page token and control sorting order.

Instructions

Search runs with filter expression and pagination

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdsNoExperiment IDs (defaults to MLFLOW_EXPERIMENT_ID)
filterNoFilter expression, e.g. "metrics.rmse < 1"
runViewTypeNo
maxResultsNoMax results (default 100)
orderByNoSort fields, e.g. ['metrics.rmse ASC']
pageTokenNo
extractFieldsNoComma-separated dotted paths with `*` wildcard (e.g. 'runs.*.info.run_id'). Reduces response tokens.
Behavior2/5

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

Lacks annotations and the description is too brief to disclose behavioral traits. For a tool with 7 parameters and no annotations, important details like filter syntax, pagination mechanics, and return format are missing.

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

Conciseness4/5

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

Single sentence is concise and front-loaded with verb and resource. It communicates the core purpose efficiently, though it could benefit from moderate expansion to cover key behavioral details.

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 no output schema and no annotations, the description is incomplete. Fails to mention return format, pagination details, or filtering capabilities, leaving significant gaps for a complex search tool.

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 description coverage is 71%, so the schema provides decent parameter documentation. However, the description adds no extra meaning beyond what the schema already states, resulting in no added value for parameter understanding.

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?

Description clearly states verb 'search' and resource 'runs', and adds key features 'filter expression' and 'pagination'. It implies a generic search capability but does not explicitly differentiate from siblings like 'search-runs-by-tags', which is a minor gap.

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?

Provides no guidance on when to use this tool versus alternatives. With many sibling search tools (e.g., search-runs-by-tags), the absence of usage context forces agents to rely on tool names alone.

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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