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mlflow-mcp-server

create-model-version

Creates a new version of a registered MLflow model. Provide model name and source artifact URI to track a model iteration.

Instructions

Create a new model version

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesRegistered model name
sourceYesArtifact source URI (e.g. 'runs:/<run_id>/model')
runIdNoSource run ID
tagsNo
runLinkNo
descriptionNo
Behavior2/5

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

Annotations indicate a write operation (readOnlyHint=false) and openness to unknown fields (openWorldHint=true). The description adds no behavioral details beyond this, such as validation behavior, side effects, or response format.

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?

The description is a single sentence with no wordiness, achieving high conciseness. However, it may be overly terse for a tool with 6 parameters.

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 a minimal description, the tool lacks crucial context such as return value, error conditions, or expected preconditions, making it incomplete for a complex operation.

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 50%, and the tool description does not add any parameter context beyond what the schema already provides. The baseline score of 3 applies as the description neither improves nor harms parameter understanding.

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 'Create' and the resource 'model version', making the purpose unambiguous. However, it does not differentiate from similar sibling tools like 'create-logged-model' or 'create-registered-model' beyond the resource name.

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 is provided on when to use this tool versus alternatives, nor are there any prerequisites mentioned (e.g., the need for an existing registered model or valid run ID).

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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