MCP server for scheduling property tours and lease qualification inquiries through multimodal channels (voice, SMS, WhatsApp, AI agent) with credit/income prequalification and property management system integration
Single tool 'execute_skill_action' has a verb-noun name (positive), but the implementation is severely underdeveloped. The tool description is 127 characters, within acceptable range, but lacks critical detail on WHEN to use it, WHAT it returns, and HOW to interpret results. Input schema is present with three string parameters, each with descriptions, but lacks enums for the 'inquiry_channel' parameter (which lists specific values like 'VOICE_SMS_MULTIMODAL', 'WHATSAPP_AI_AGENT'). No output schema is documented anywhere in the source. The client.py mock returns a complex object with 7 fields (lease_inquiry_id, prospective_tenant, inquiry_channel, selected_unit, credit_income_prequalification_passed, self_guided_smart_lock_tour_booked_time, property_management_yardi_realpage_synced, leasing_conversion_rate_lift_pct), but this structure is never declared in the tool definition. No error handling, no recovery guidance, no validation rules. The mcp_server.py is a stub that only prints a JSON status message, it does not actually implement the MCP protocol or handle tool invocations. This is a proof-of-concept, not a production tool.
Execute leasing multimodal inquiry scheduling and property tour booking with lease qualification
No output schema documented. Tool returns 8 fields (lease_inquiry_id, prospective_tenant, inquiry_channel, selected_unit, credit_income_prequalification_passed, self_guided_smart_lock_tour_booked_time, property_management_yardi_realpage_synced, leasing_conversion_rate_lift_pct) but LLM has no way to know what to expect.
inquiry_channel parameter accepts only specific values (VOICE_SMS_MULTIMODAL, WHATSAPP_AI_AGENT, etc.) but is defined as a free-form string with no enum constraint. LLM will hallucinate invalid channel names.
Tool description (127 chars) lacks WHEN to use it, WHAT it does in detail, and WHAT it returns. Does not answer: 'What does it do? When should the LLM call it? What does it return?'
No error handling or recovery guidance. If the tool fails (e.g., tenant not found, unit unavailable, qualification fails), the LLM receives no actionable error message or next steps.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 37 | 2026-07-28+ | v2 |
mcp_server.py is a stub that only prints a status message. It does not implement the MCP protocol, handle tool invocations, or call the actual client logic. The server is non-functional.