Skip to main content
Glama
kkruglik

MLflow MCP Server

by kkruglik

set_model_alias

Idempotent

Assign an alias like 'champion' to a specific model version to promote or label it for deployment.

Instructions

Assign an alias to a specific model version (e.g. promote best model to 'champion').

Args: name: Name of the registered model. alias: Alias to assign, e.g. 'champion', 'production', 'baseline'. version: Model version number to assign the alias to.

Examples: set_model_alias("lightgbm", "champion", "3")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
aliasYes
versionYes
Behavior3/5

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

Annotations set readOnlyHint=false (mutates) and idempotentHint=true. Description says 'assign', which aligns with mutation. No additional behavioral context is provided beyond what annotations already convey. No contradictions.

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?

Description is concise: one-line summary, Args list, and an example. Every sentence is purposeful and front-loaded with the key action.

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?

For a simple mutation tool with 3 parameters and idempotent annotations, the description covers usage adequately. It does not mention return value (no output schema) or behavior on reassignment, but overall it's nearly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, so description compensates by listing each parameter with brief explanations (name, alias, version) and includes an example. This adds meaning beyond the schema's type-only definitions.

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?

Description clearly states 'Assign an alias to a specific model version' with an example ('promote best model to champion'). This is a specific verb+resource that distinguishes from sibling tools like delete_model_alias or get_model_version_by_alias.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an example but does not explicitly specify when to use this tool vs alternatives (e.g., transition_model_version_stage). It implies usage for assigning aliases but lacks when-not guidance. Clear context but no 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/kkruglik/mlflow-mcp'

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