RunAPI GPT Image 2 MCP server for image generation: create tasks, poll results, and check pricing across 1 model from Claude Code, Codex, Cursor, and VS Code.
Two tools with basic schemas and descriptions, but significant gaps in parameter documentation and error handling. get_task has optional parameters with minimal guidance on defaults and dependencies. check_pricing lacks clarity on what 'model' and 'action' mean in context. Neither tool documents output structure or error recovery paths. Descriptions are present but generic (avg ~80 chars, below the 194-char baseline for A+ tools). No parameter descriptions visible in the schema, only inline type hints. No error handling guidance or recovery suggestions.
Look up RunAPI pricing for the gpt-image-2 model line.
Fetch the current status and latest result payload for a gpt-image-2 task.
Parameter descriptions missing from schemas. 'task_id' and 'action' in get_task, 'model' and 'action' in check_pricing have no inline descriptions explaining what values are valid, what format is expected, or how defaults work.
Output schema not documented. Neither tool specifies what fields the response contains, their types, or how to chain results to other tools. LLMs cannot plan downstream calls without knowing response structure.
No error handling guidance. Code catches errors and returns friendlyError(), but tool descriptions do not explain what errors are possible, whether they are retryable, or what the LLM should do next.
Ambiguous parameter semantics. 'action' parameter in both tools defaults based on contract state, but descriptions do not explain when the default applies, what happens if omitted with multiple endpoints, or how to discover valid values.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 49 | 2026-07-28+ | v2 |
Generic tool descriptions lack context. 'Fetch the current status...' and 'Look up RunAPI pricing...' do not explain when to use these tools, what prerequisites exist, or what the typical workflow is.