Model Context Protocol Server for monitoring Operational Status of major digital platforms in Claude Desktop
This MCP server exposes a single tool 'status' with a simple parameter interface. However, critical quality gaps significantly limit its usefulness: (1) The tool description is generic and lacks actionable context about when/why to use it or what it returns. (2) The input schema defines only a 'platform' parameter as a free-form string with no enum constraint, despite the server supporting 10+ known platforms (amplitude, anthropic, asana, atlassian, cloudflare, digitalocean, discord, docker, dropbox, gcp, gemini, etc.). This forces the LLM to hallucinate valid platform names. (3) No output schema is documented anywhere, the source code shows multiple response interface definitions (AnthropicStatusResponse, AtlassianStatusResponse, etc.) but the tool definition does not declare what structure the LLM should expect. (4) Parameter description is terse ('The platform ID to check status for (e.g. 'github', 'slack', 'openai'). Use 'list' to see all available platforms.'), it includes example values (github, slack, openai) which LLMs tend to reuse literally, yet only 2 of these (github is not in the platform map, slack is missing) appear to be implemented. (5) Error handling is not visible in the tool definition, no guidance on what happens if platform not found, what to do next, or how to discover valid platforms. The source code does show fetching from external status APIs but no error recovery strategy in the tool layer.
Check the operational status of a specific platform or list all available platforms
No enum constraint on 'platform' parameter despite 10+ supported platforms. Free-form string invites hallucinated values (e.g., 'github' is mentioned in description but not in initializePlatforms map).
No output schema documented. Multiple response interfaces exist in code (AnthropicStatusResponse, DockerStatusResponse, etc.) but tool definition provides no guidance on what fields LLM should expect or how to extract status from the response.
Tool description includes example values (github, slack, openai) that are not all implemented. LLMs latch onto examples and pass them literally, causing runtime failures.
No error handling guidance. Tool description does not explain what to do if a platform is not found, how to recover, or how to list available platforms programmatically.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 40 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 0 | - | v1 |
Parameter description is generic and lacks actionable context. Does not explain what the response contains, when to call 'list' vs normal platform query, or what constitutes valid output.