This MCP server has a single tool 'score_post' with critical definition gaps. The tool name is adequate (score_post starts with verb), but descriptions are sparse, parameter annotations are minimal, and no output schema is documented. The implementation is a simple Python class without MCP framework integration visible, this appears to be a stub or proof-of-concept rather than a production MCP server. No MCP protocol registration, no error handling patterns, no recovery guidance.

• Expand tool description to 100 - 200 chars: 'Analyzes social media post content and metadata to estimate engagement reach (0.1 - 10.0 scale). Considers text length, hashtag usage, and media presence. Returns structured engagement score and prioritized optimization suggestions to maximize visibility.',
• Document the output schema explicitly: { engagement_score: number (range 0.1 - 10.0), suggestions: array of strings, reasoning: { score_components: { base_score, image_bonus, hashtag_bonus, length_penalty }, total_adjustments: number } }
• Enhance parameter descriptions: post_copy → 'Social media post text content (0 - 300 characters recommended; longer posts receive engagement penalty). Include hashtags (#tag) for search indexing boost.', has_images → 'Boolean flag indicating presence of image, video, or rich media assets. Posts with media receive +3.0 score bonus. Required.'
• Add explicit scoring constraints to description: 'Returns engagement_score clamped to 0.1 - 10.0 range. Baseline 3.0 + bonuses (images +3.0, hashtags +1.5, short copy +1.5) - penalties (long copy >200 chars: -1.0).'
• Wrap the Python class in an actual MCP framework (e.g. mcp-sdk-python, mcp, or similar) to register as a proper MCP server with tool schemas, request/response handlers, and protocol compliance.
• Add error handling for edge cases: empty post_copy, has_images null/invalid, extremely long inputs (>5000 chars). Return actionable error messages like 'Post copy exceeds maximum length (5000 chars); truncate or split content.'