Hong Kong Health Data MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_aed_waiting_timesA | Get current Accident and Emergency Department waiting times by hospital in Hong Kong |
| get_specialist_waiting_timesA | Get current waiting times for new case bookings for specialist outpatient services by specialty and cluster in Hong Kong |
| get_pas_gopc_avg_quotaA | Get average number of general outpatient clinic quotas for the preceding 4 weeks across 18 districts in Hong Kong |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool targets a distinct health service resource: AED waiting times, specialist outpatient waiting times, and general outpatient clinic quotas. There is no overlap in purpose or data returned.
The first two tools follow a clear 'get_<service>_waiting_times' pattern, but the third tool deviates with 'get_pas_gopc_avg_quota' using a different structure. Still, all use the 'get_' prefix and are readable.
With only three tools, the server is tightly focused on Hong Kong public health waiting times and quotas. Each tool addresses a distinct data need, making the count well-scoped for its niche purpose.
The server covers the main public waiting time categories: A&E, specialist outpatient, and general outpatient clinics. Minor gaps exist such as private healthcare or specific procedure wait times, but the core domain is reasonably complete.