Skip to main content
Glama
us-all

mlflow-mcp-server

by us-all

log-metric

Record a numeric metric for a specific run, with optional timestamp and step. Required parameters: run ID, metric name, and value.

Instructions

Log a single metric value to a run

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdYes
keyYesMetric name
valueYesMetric value
timestampNoUnix timestamp ms (defaults to now)
stepNoStep at which metric was recorded
Behavior2/5

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

No annotations present; description fails to disclose behavioral aspects like overwriting behavior, timestamp handling, or run status requirements.

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?

A single sentence that is efficient, though it could be slightly expanded to include key parameter context without becoming verbose.

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?

Adequate for a simple tool but lacks explicit mention of required parameters and does not explain return behavior or run validity.

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 80%, so baseline is 3. Description adds no extra meaning beyond the schema; runId lacks description in both schema and description.

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 it logs a single metric value to a run, distinguishing it from sibling tools like log-batch and log-param.

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 alternatives like log-batch or log-param; no context on prerequisites or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/us-all/mlflow-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server