KMB Bus MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: finding buses to destinations, searching stops by name, getting routes at a stop, checking next bus arrivals, and listing stops on a route. The descriptions reinforce these unique functions, making misselection unlikely.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with underscores (e.g., find_buses_to_destination, get_route_stops_info). The naming is uniform and predictable, using clear action verbs like 'find' and 'get' paired with descriptive nouns.
Tool Count5/5
With 5 tools, this server is well-scoped for a bus information system. Each tool serves a specific, necessary function in querying routes, stops, and schedules, avoiding bloat while covering core use cases effectively.
Completeness4/5
The tool set covers essential bus information queries: route discovery, stop lookup, schedule checking, and route details. A minor gap exists in lacking tools for broader operations like route planning or real-time updates, but agents can work around this with the provided tools.
Average 3.4/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Find bus routes') but lacks details on traits like response format, pagination, rate limits, error conditions, or whether it's a read-only operation. This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first followed by parameter details. The two sentences are efficient and focused, with no wasted words, though the structure is simple without explicit sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (1 parameter, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameter semantics adequately, but lacks behavioral context and usage guidelines. The presence of an output schema reduces the need to explain return values, but more guidance is still warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains the 'destination' parameter with examples ('Central', 'Mong Kok', 'Airport'), clarifying the expected input format and scope. This compensates well for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Find') and resource ('bus routes'), and specifies the target ('to a specified destination'). It doesn't explicitly differentiate from sibling tools like 'get_all_routes_at_stop' or 'get_route_stops_info', but the destination-focused search is reasonably distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'find_stop_by_name' or 'get_all_routes_at_stop', nor does it specify prerequisites or exclusions (e.g., whether it requires real-time data or works with schedules only).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what the tool does (retrieves arrival time) but lacks critical behavioral details: it doesn't specify if this requires real-time data access, whether results are cached, what happens if the route/stop doesn't exist, or if there are rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operational behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose clearly, followed by a structured 'Args' section that efficiently documents parameters with examples. Every sentence earns its place without redundancy or fluff, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 required parameters, no annotations, but with an output schema), the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context (e.g., error handling, data freshness). The presence of an output schema means the description doesn't need to explain return values, but it should still address usage guidelines and operational traits to be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful semantics beyond the input schema. The schema has 0% description coverage (only titles 'Route' and 'Stop Name'), but the description provides concrete examples for 'route' (e.g., '1A', '6', '960') and clarifies that 'stop_name' is the name of the bus stop. This compensates well for the low schema coverage, though it doesn't detail format constraints (e.g., case sensitivity).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the next arrival time for a specified bus route at a stop.' It includes a specific verb ('Get'), resource ('next arrival time'), and scope ('bus route at a stop'). However, it doesn't explicitly differentiate from sibling tools like 'get_all_routes_at_stop' or 'find_buses_to_destination', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_all_routes_at_stop' (which might list all routes at a stop) or 'find_buses_to_destination' (which might prioritize destination over route). Without any context on usage scenarios or exclusions, the agent must infer based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what the tool does ('Get all stops') without mentioning any behavioral traits such as whether it's read-only, potential rate limits, error handling, or what the output contains. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated clearly in the first sentence. The parameter explanation is concise and directly relevant. It could be slightly improved by integrating the parameter details more seamlessly, but it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema, the description is minimally adequate. However, it lacks context about behavioral aspects (e.g., read-only nature, error cases) and doesn't leverage sibling tool names to guide usage, leaving gaps in completeness despite the output schema handling return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant value beyond the input schema, which has 0% description coverage. It explains the 'route' parameter as 'The bus route number' and provides concrete examples (e.g., '1A', '6', '960'), clarifying the expected format and semantics that the schema alone does not cover.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('all stops along a specified bus route'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_all_routes_at_stop' or 'find_stop_by_name', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_all_routes_at_stop' (which might provide overlapping information) or clarify scenarios where this tool is preferred, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states what the tool does but doesn't describe response format, error handling, rate limits, or whether it requires authentication. For a read operation with no annotation coverage, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences: one stating the purpose and another documenting the parameter. It's front-loaded with the core functionality, though the parameter documentation could be integrated more seamlessly rather than as a separate 'Args' section.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete behavioral transparency, it doesn't fully prepare an agent for edge cases or system constraints, leaving room for improvement in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful context for the single parameter 'stop_name' by explaining it's 'Name of the bus stop', which clarifies its purpose beyond the schema's basic title. With 0% schema description coverage and only one parameter, this adequately compensates, though it doesn't detail format constraints (e.g., case sensitivity).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get all bus routes') and resource ('that pass through a specified bus stop'), making the purpose immediately understandable. It distinguishes from sibling tools like 'find_stop_by_name' (which finds stops) and 'get_next_bus' (which provides timing information) by focusing on route enumeration at a stop.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'find_buses_to_destination' or 'get_route_stops_info'. It lacks context about prerequisites (e.g., whether the stop must exist in the system) or exclusions (e.g., not for real-time bus tracking).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a search operation but lacks details on permissions, rate limits, pagination, or return format. The description does not contradict annotations, but it provides minimal behavioral context beyond the basic operation, which is insufficient for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the first sentence stating the tool's purpose clearly. The second sentence provides essential parameter details without redundancy. Every sentence earns its place, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is largely complete. It covers purpose and parameter semantics adequately. However, the lack of behavioral details (e.g., search behavior, limitations) and usage guidelines slightly reduces completeness, though the output schema mitigates some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explicitly explains that 'stop_name' is for 'Full or partial name of the bus stop to search for', clarifying the parameter's purpose and usage, which compensates fully for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Find') and resource ('bus stops'), specifying it matches by 'name or partial name'. It distinguishes from siblings like 'get_all_routes_at_stop' (which focuses on routes) and 'find_buses_to_destination' (which focuses on buses), making it highly specific and differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching bus stops by name, but does not explicitly state when to use this tool versus alternatives like 'get_route_stops_info' (which might provide stop details within a route context) or 'get_all_routes_at_stop' (which focuses on routes at a specific stop). No exclusions or prerequisites are mentioned, leaving usage context somewhat inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp_hkbus MCP server](https://glama.ai/mcp/servers/kennyckk/mcp_hkbus/badges/card.svg)](https://glama.ai/mcp/servers/kennyckk/mcp_hkbus)

Score Badge

Copy to your README.md:

[![mcp_hkbus MCP server](https://glama.ai/mcp/servers/kennyckk/mcp_hkbus/badges/score.svg)](https://glama.ai/mcp/servers/kennyckk/mcp_hkbus)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kennyckk/mcp_hkbus'

If you have feedback or need assistance with the MCP directory API, please join our Discord server