list_modelsList available Modelflare API models your key can call, with docs links and request contracts; filter by image, video, or text, defaulting to image and video.
Lists the models this Modelflare API key can call, with the docs page that holds each media model's exact request contract. Defaults to image and video models.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | Only list models of this kind. |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely new behavioral context: results are scoped to what the API key is authorized to call, the filter defaults to image+video rather than returning everything, and the response carries a docs page with each model's exact request contract.
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?
Two sentences, front-loaded with the core action and scoped by the API key before mentioning the filter default. The phrase 'with the docs page that holds each media model's exact request contract' is slightly long but carries useful information about the return value, so it 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?
For a one-optional-parameter, read-only discovery tool with no output schema, the description covers scope, authorization bounds, default filtering behavior, and the key content of the response (docs/request contract). An agent can call it correctly, though it could go one step further and position it as the prerequisite step for the generation siblings.
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?
Schema coverage is 100% and the enum values are self-documenting, so the baseline would be 3. The description nonetheless adds semantics the schema lacks: what the result set looks like when kind is omitted (image and video only), which resolves the default-value question for the single optional parameter.
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?
States a specific verb and resource: lists the Modelflare models the current API key can call, and adds that the payload includes each media model's docs URL. That scope is clearly distinct from the generation/status siblings (create_video, generate_image), though the description never names those siblings explicitly to route the agent.
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 only usage signal is the implicit default ('Defaults to image and video models'), which tells the agent what happens when the kind filter is omitted. There is no explicit guidance such as 'call this first to discover valid model identifiers before generate_image/create_video', and no statement of when NOT to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.