Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Hong Kong Government Environment MCP Server What's the current Air Quality Health Index in Hong Kong?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This is an MCP server that provides access to Hong Kong government environment data through a FastMCP interface.
Air Quality Health Index (AQHI): Retrieve current AQHI data from general and roadside air quality monitoring stations across Hong Kong. The AQHI is reported on a scale of 1 to 10 and 10+, grouped into five health risk categories with corresponding health advice.
Related MCP server: mcp-hko
Hong Kong Environmental Protection Department (EPD): For AQHI and other environmental data.
Here are some example prompts you can use to interact with this MCP server through Cline or other compatible interfaces:
AQHI Data: "What is the current Air Quality Health Index in Hong Kong?"
Clone this repository to your local machine.
Install Python dependencies:
pip install -r requirements.txtRun the server:
python server.pyDefault stdio mode: python server.py
SSE mode (port 8000): python server.py --sse
To connect this MCP server to Cline using stdio:
Add this configuration to your Cline MCP settings (cline_mcp_settings.json):
{
"hk-environment": {
"disabled": false,
"timeout": 3,
"type": "stdio",
"command": "uvx",
"args": [
"hkopenai.hk-environment-mcp-server"
]
}
}This configuration allows Cline to communicate with the server and utilize its tools for data retrieval.
Tests are available in the tests/ directory. Run with:
pytestCurrent Air Quality Health Index (AQHI) at individual general and roadside Air Quality Monitoring stations in Hong Kong. The AQHIs are reported on a scale of 1 to 10 and 10+ and are grouped into five AQHI health risk categories with health advice provided.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral burden. It usefully discloses the data granularity (individual stations), the measurement scale (1 to 10 and 10+), and the health risk categories with advice. It does not mention data freshness or update frequency, but for a simple read-only current-data tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a compact two-sentence definition that front-loads the key fact: this is current AQHI data. It could be slightly more direct by using an imperative verb, but there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter read-only tool with an output schema, the description covers the essential context: what is measured, where, the scale, and the categorization. Nothing critical is missing for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. No parameter guidance is needed, and the description appropriately focuses on the output semantics instead.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource: current AQHI readings at individual general and roadside monitoring stations in Hong Kong. It lacks an explicit verb like 'retrieves' or 'returns,' but the meaning is unambiguous. With no sibling tools, differentiation is not needed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is the tool for obtaining current AQHI values in Hong Kong, but it does not explicitly state when to use it versus alternatives or mention any exclusions. There are no sibling tools to contrast with, so this is a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.8get_current_aqhiWith only a single tool, there is no possibility of confusion between tools. The tool's purpose is clearly scoped to retrieving the current AQHI.
The lone tool name follows a clear verb_noun pattern: get_current_aqhi. There is no other tool to create inconsistency.
The server presents itself as a general environment MCP for Hong Kong, yet it exposes only one tool for air quality. This is too few for the apparent scope, making the server feel extremely thin.
Only current AQHI readings are provided, with no historical data, forecasts, or coverage of other environmental domains. The surface is severely incomplete for an environment-focused server.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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