Skip to main content
Glama
log-10x

Log10x MCP Server

Official

Discover labels

log10x_discover_labels
Read-onlyIdempotent

Lists filterable/groupable Log10x metric labels and returns distinct values for a given label. Call before label queries to avoid guessing wrong names like namespace vs k8s_namespace.

Instructions

List the labels Log10x metrics can be filtered or grouped by. Call at the start of a session, or before calling any tool that takes a label/filter argument: stops the model from guessing label names like "namespace" when the label is "k8s_namespace". Pass a label name to get its distinct values.

Input Schema

NameRequiredDescriptionDefault
labelNoIf set, return distinct values for this label (e.g., "tenx_user_service" returns every service). If omitted, return the full label name list.
limitNoMax values to return when a label is specified.
environmentNoEnvironment nickname (for multi-env setups).

Output Schema

NameRequiredDescriptionDefault
dataNo
toolYes
viewNosummary
imagesNo
actionsNo
summaryYes
warningsNo
truncatedNo
next_cursorNo
render_hintNo
generated_atYes
schema_epochYes
schema_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.30.7

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and openWorld, so the safety profile is covered. The description adds real value beyond that: it discloses the dual behavior (full label list vs. distinct values when a label is passed) and the motivating failure mode (guessing "namespace" instead of "k8s_namespace").

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?

Three short sentences, front-loaded with purpose, then usage, then the mode switch. The concrete "namespace" vs "k8s_namespace" example earns its place by making the anti-guessing rationale vivid, and nothing is padded.

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

Completeness5/5

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

Output schema exists, so return formats need no explanation, and annotations carry the safety profile. Purpose, session-start usage, and the label-mode distinction are all present – an agent has everything needed to call it correctly.

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 100% and the properties already document label, limit (default/max), and environment in detail. "Pass a label name to get its distinct values" largely restates the schema's own text, so the description adds little beyond the structured fields – baseline 3 is appropriate.

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?

States a specific verb and resource: "List the labels Log10x metrics can be filtered or grouped by." The resource (labels for metric filtering/grouping) is precise and clearly distinct from the other discover_* siblings (discover_env, discover_join), and it also reveals the second mode (distinct values per label).

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?

Gives a concrete trigger: "Call at the start of a session, or before calling any tool that takes a label/filter argument," which is exactly the context an agent needs. It does not name when-not-to-use or explicitly route to an alternative tool, so it falls just short of the 5 bar.

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