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mlflow-mcp-server

by us-all

search-traces

Search and filter traces in experiments by experiment IDs and filter expressions to retrieve targeted results.

Instructions

Search and filter traces in experiments

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experimentIdsNoExperiment IDs (defaults to MLFLOW_EXPERIMENT_ID)
filterNoFilter expression, e.g. "tags.user = 'alice'"
maxResultsNoMax results (default 100)
orderByNo
pageTokenNo
extractFieldsNoComma-separated dotted paths with `*` wildcard, e.g. "traces.*.trace_id".
Behavior2/5

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

No annotations provided. The description does not disclose read-only nature, pagination behavior (pageToken), effect of filtering, or error handling. It does not address behavioral traits beyond the basic search function.

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 description is a single short sentence, which is concise but under-specified for 6 parameters and no annotations. It is not unnecessarily verbose, but lacks structure (e.g., sections for usage, parameters, behaviour).

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?

With no output schema and minimal description, the agent cannot understand return format or trace schema. The description omits details on filtering behavior, pagination, and field extraction output, making it incomplete for a medium-complexity 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 coverage is 67%. The description adds value by clarifying maxResults default and filter syntax, and adding extractFields format. However, orderBy and pageToken lack descriptions, and the description does not fully compensate for remaining gaps.

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 description clearly states the action ('search and filter') and resource ('traces') with scope ('in experiments'). It is not a tautology and distinguishes from generic search tools, though it could be more specific about the trace domain.

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?

No guidance on when to use this tool vs. other search tools (e.g., search-runs) or trace-specific tools (e.g., get-trace). No mention of alternatives, prerequisites, or context for selecting this tool.

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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