Flint Chart MCP demonstrates solid definition quality with well-named, verb-led tools and detailed parameter descriptions. All 6 tools have clear, substantive descriptions (150-300 chars) aligned with the rubric baseline (avg 194 chars). Input schemas are present and properly typed with enums for backend/format parameters. However, output schemas are not explicitly documented in the visible source code, and tool annotations (readOnlyHint, destructiveHint, idempotentHint) are absent despite all tools being read-only operations. Error handling strategy is not evident from the provided code samples. The toolset is well-composed with clear single responsibilities and good parameter naming conventions (chartType, encoding, backend follow verb_noun patterns).

• Document output schemas for all tools. For render_chart: { image: string (base64), format: string, width: number, height: number }. For compile_chart: { spec: object, warnings: string[], layout: { width, height } }. For list_chart_types: { types: [{ name, channels: [...], constraints: {...} }], total: number }. For create_chart_view: { viewUrl: string, interactiveHtml: string }.
• Add tool annotations in MCP request/response. Register each tool with { readOnlyHint: true } in the _meta or response envelope, signaling that all 6 tools are safe to retry and have no side effects.
• Expand parameter 'data' description to clarify both cases: 'Either an object { values: Array<Record<string, any>> } with inline data rows, or an object { url: string } with a URL pointing to a JSON or CSV file. If url is provided, the file is fetched and parsed server-side.'
• Specify result limits and pagination for discovery tools. 'list_chart_types returns all available types (typically 8-20). If the list grows, add optional limit and offset parameters.' Similarly for list_themes.
• Add error handling examples to tool descriptions. E.g., render_chart: 'On invalid backend or format, returns { error: string }. On missing data or invalid encoding, returns { error: string, suggestion: string }.' This guides LLM error recovery.
• Consider adding a 'validate_and_render' wrapper that runs validation before rendering, returning validation errors early to prevent wasted rendering calls on invalid specs.
• Document backend capabilities and constraints in list_chart_types response. E.g., chartjs supports PNG only (not SVG); plotly requires browser context; excel returns a workbook file. This helps LLMs pick the right backend for the intended output.