CATA Bus MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting different aspects of bus system data: health checks, data initialization, route listing, arrival queries, stop searches, alert retrieval, and vehicle tracking. There is no overlap in functionality that would cause agent confusion.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., list_routes_tool, search_stops_tool, trip_alerts_tool), but 'health_check' and 'initialize_data' deviate by lacking the '_tool' suffix. The naming is still readable and mostly predictable.
Tool Count5/5
With 7 tools, this server is well-scoped for a bus transit system, covering essential operations like health monitoring, data management, route information, stop searches, arrival times, alerts, and vehicle positions without being overwhelming or insufficient.
Completeness4/5
The toolset provides comprehensive coverage for real-time bus system queries, including data initialization, route and stop information, arrivals, alerts, and vehicle tracking. A minor gap exists in lacking update or deletion tools for data management, but this is reasonable for a read-focused transit API.
Average 3.3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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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 full burden. While it mentions the tool searches and returns a list, it doesn't disclose important behavioral traits like whether this is a read-only operation, if there are rate limits, authentication requirements, or how results are sorted/paginated. The description is minimal on behavioral context.
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 concise with clear sections for Args and Returns. Both sentences earn their place by explaining the parameter and return value. However, the structure could be slightly improved by integrating the information more fluidly rather than as separate labeled 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 has an output schema (which handles return values) and only one parameter with decent semantic coverage in the description, the description is moderately complete. However, for a search tool with no annotations, it lacks important context about search behavior, limitations, and when to use versus siblings.
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?
With 0% schema description coverage, the description compensates well by explaining that the 'query' parameter matches against stop names, IDs, or descriptions. This adds meaningful semantic context beyond the bare schema type, though it doesn't specify format examples or search behavior details.
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 as searching for stops by name or ID, which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'list_routes_tool' or 'vehicle_positions_tool' that might also involve stop-related data.
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. With siblings like 'list_routes_tool' and 'next_arrivals_tool' that might involve stops, there's no indication of when search is preferred over listing or when other tools might be more appropriate.
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. It mentions 'ultra-fast' and 'optimized for cloud pre-flight validation,' which gives some behavioral context, but lacks details on permissions, rate limits, error handling, or what the health check entails. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads key information ('Ultra-fast health check') without unnecessary words. Every part earns its place, making it highly concise and well-structured.
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 has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, for a health check tool with no annotations, it should provide more context on what is checked, success criteria, or typical use cases to be fully complete, especially compared to siblings.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, which is appropriate, but it could have mentioned if any implicit inputs are required. Baseline is 4 for zero parameters, as the schema fully covers the absence of inputs.
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 performs a 'health check' with the specific purpose of 'cloud pre-flight validation' and mentions it's 'ultra-fast.' This provides a clear verb ('health check') and context, though it doesn't explicitly differentiate from sibling tools like 'initialize_data' or 'list_routes_tool,' which prevents a score of 5.
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 implies usage for 'cloud pre-flight validation' but does not specify when to use this tool versus alternatives like 'initialize_data' or other siblings. There is no explicit guidance on prerequisites, timing, or exclusions, leaving the agent with minimal context for tool selection.
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. While 'manually trigger' implies a write operation, it doesn't specify whether this is idempotent, what permissions are needed, what side effects occur, or how long initialization takes. For a mutation tool with zero annotation coverage, this is inadequate.
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 a single, efficient sentence with no wasted words. It's appropriately sized and front-loaded, making it easy 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 has an output schema (which handles return values) and no parameters, the description is minimally adequate. However, as a mutation tool with no annotations, it should provide more behavioral context (e.g., idempotency, side effects) to be fully 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?
There are 0 parameters, and schema description coverage is 100%, so the schema already fully documents the lack of inputs. The description doesn't need to add parameter details, earning a baseline score of 4 for zero-parameter tools.
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 action ('manually trigger') and resource ('GTFS data initialization'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from its siblings (like health_check or list_routes_tool), which would require a 5.
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 or any context about prerequisites. It merely states what the tool does without indicating appropriate usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves 'current' alerts, implying real-time or recent data, and mentions the return format. However, it lacks details on rate limits, authentication needs, data freshness, or error handling, which are important for behavioral understanding.
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 well-structured and front-loaded with the purpose, followed by parameter and return details. It uses minimal sentences that earn their place, though the 'Args:' and 'Returns:' sections could be integrated more seamlessly into the flow for slightly better conciseness.
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 optional parameter) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose, parameter semantics, and return structure, though it could benefit from more behavioral context like data sources or update frequency.
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 schema description coverage is 0%, so the description must compensate. It explains the 'route_id' parameter as 'Optional route ID to filter alerts (if None, returns all)', adding clear meaning beyond the schema. This adequately covers the single parameter, though it doesn't specify format or examples.
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 current service alerts.' It specifies the verb ('Get') and resource ('service alerts'), making the function unambiguous. However, it doesn't explicitly differentiate this tool from its siblings (e.g., 'list_routes_tool'), 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 mentions an optional 'route_id' parameter for filtering but doesn't explain scenarios where filtering is beneficial or when other tools might be more appropriate. This lack of contextual guidance limits its utility for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return format ('list of routes with their ID, short name, long name, and color'), which is useful behavioral context. However, it doesn't mention potential limitations like pagination, rate limits, or data freshness, which are important for a list operation.
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 extremely concise and well-structured: two sentences that directly state the purpose and return format without any fluff. Every word earns its place, 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, output schema exists), the description is reasonably complete. It explains what the tool does and what it returns, which is sufficient for basic understanding. However, it could improve by addressing behavioral aspects like data scope or limitations, slightly reducing 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 tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately avoids discussing parameters, earning a high baseline score for not adding unnecessary information.
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: 'List all available bus routes.' It specifies the verb ('List') and resource ('bus routes'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search_stops_tool' or 'vehicle_positions_tool', 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 prerequisites, context for usage, or comparisons to siblings like 'search_stops_tool' for filtered results. This lack of usage context leaves the agent without clear direction.
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 mentions the return format but doesn't cover critical aspects like error handling, rate limits, authentication needs, data freshness, or whether this is a read-only operation. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 perfectly structured and front-loaded with the core purpose, followed by organized sections for Args and Returns. Every sentence earns its place with zero wasted words, making it highly efficient and easy to parse.
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, no annotations, and the presence of an output schema (which handles return value documentation), the description is adequate but incomplete. It covers parameters well but lacks behavioral context and usage guidelines, making it minimally viable but with clear gaps.
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 that stop_id is 'The stop ID to query' and horizon_minutes defines 'How many minutes ahead to look (default 30)', providing clear semantic meaning that compensates for the schema's lack of descriptions.
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 next arrivals') and resource ('at a specific stop'), distinguishing it from sibling tools like list_routes_tool or search_stops_tool. It precisely defines what the tool does without being vague or tautological.
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 trip_alerts_tool or vehicle_positions_tool. It lacks context about prerequisites, exclusions, or typical use cases, offering only basic functional information without comparative guidance.
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 read operation ('Get') but does not cover important aspects such as whether this requires authentication, rate limits, data freshness, error handling, or pagination. The description adds 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 core purpose stated first, followed by structured Args and Returns sections. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse.
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 moderate complexity (single parameter, read-only operation) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, parameter semantics, and return structure, though it lacks behavioral details like authentication or rate limits. With output schema reducing the need to explain returns, the description is adequate but could be more comprehensive.
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, which has 0% description coverage. It explains that route_id is 'The route ID to filter by' and provides an example ('e.g., "BL" for Blue Loop'), clarifying its purpose and format. With only one parameter, this compensation is adequate, though not exhaustive (e.g., no validation rules).
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 ('current positions of vehicles on a specific route'). It distinguishes from siblings like list_routes_tool (which lists routes) and next_arrivals_tool (which provides arrival times), though it doesn't explicitly name these alternatives. The purpose is not vague or tautological.
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 context by specifying 'on a specific route' and providing an example route_id, but it does not explicitly state when to use this tool versus alternatives like next_arrivals_tool or trip_alerts_tool. There is no guidance on prerequisites, exclusions, or named alternatives, leaving usage somewhat inferred rather than clearly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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