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Read-only

Find MLflow MCP tools by natural language query. Returns matching tool names and descriptions to navigate the 77+ tool surface efficiently.

Instructions

Discover available tools by natural language query. Returns matching tool names + descriptions across all categories. Use this first to navigate the 77+ tool surface efficiently.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language query. Discover tools across the MLflow MCP surface (experiments, runs, registry, traces, assessments, webhooks, prompts).
categoryNoRestrict search to a specific category
limitNoMax results (default 20)
Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, which cover the key behavioral traits. The description adds that it returns 'matching tool names + descriptions', which is consistent with annotations. No extra behavioral context is provided, but no contradictions exist.

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 exceptionally concise: two sentences with zero waste. The first sentence conveys the core purpose, and the second adds immediate usage guidance. It is well front-loaded and earns its brevity.

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

Completeness4/5

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

Given the tool's simplicity and the comprehensive schema/annotations, the description covers the essential aspects: what it does and when to use it. It does not describe return format, but for a search tool this is acceptable. Overall, it is sufficiently complete for the context.

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 100%, with all three parameters documented. The description does not add meaning beyond the schema; it merely repeats the concept of 'natural language query'. Baseline 3 applies as the schema carries the full parameter information.

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 uses the specific verb 'Discover' and resource 'available tools', clearly stating it performs natural language search across all categories. It distinguishes itself from sibling tools by explicitly positioning it as a first-step navigation aid for the 77+ tool surface.

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?

The description tells the agent to use this tool first to efficiently navigate the large tool surface. While it doesn't explicitly state when not to use it or name alternatives, the directive 'Use this first' provides clear context for appropriate use.

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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