health
Verify MLflow server status and connectivity to ensure the server is reachable and operational.
Instructions
Check MLflow server health and connectivity
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Verify MLflow server status and connectivity to ensure the server is reachable and operational.
Check MLflow server health and connectivity
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds 'connectivity' to the read-only nature indicated by annotations, providing slight extra context. No contradictions. It is adequate given the simplicity of the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 5-word sentence with no extraneous information. It is efficiently front-loaded and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema, read-only annotation), the description is complete. It tells the agent exactly what the tool does.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description does not need to add parameter information; it suffices baseline score 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check MLflow server health and connectivity' clearly states the action (check) and the resource (MLflow server health/connectivity). It distinguishes the tool from its siblings, which are focused on runs, experiments, and models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for verifying server status before other operations, but it does not explicitly state when to use this tool versus alternatives or provide any exclusions. Usage is implied but not detailed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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'
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