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anoopt

TfL Journey Status MCP Server

by anoopt
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation2/5

    The tools 'get_line_status' and 'get_line_status_detail' have significant overlap in purpose, both retrieving line status information with only a vague distinction in detail level. This creates ambiguity for an agent trying to choose between them, as the descriptions don't clearly differentiate when to use each tool.

    Naming Consistency4/5

    All three tools follow a consistent verb_noun naming pattern with snake_case. 'get_line_status' and 'get_line_status_detail' share the same verb prefix, while 'plan_journey' uses a different but still clear verb. The naming is mostly consistent with only minor deviation in verb choice.

    Tool Count3/5

    With only 3 tools, this server feels thin for a transportation domain that typically involves multiple operations. While the core functions are present, the count is borderline low for what could be a more comprehensive TfL API surface covering additional journey planning or status features.

    Completeness2/5

    For a TfL journey status server, there are significant gaps in coverage. Missing are tools for station information, arrival predictions, service disruptions beyond line status, and journey planning variations (like alternatives or real-time updates). The surface provides only basic line status and journey planning, leaving many common transportation queries unaddressed.

  • Average 3/5 across 3 of 3 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 status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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?

    With no annotations provided, the description carries full burden but only states it retrieves status without detailing behavioral traits like rate limits, error handling, authentication needs (beyond the optional app_key parameter), or response format. It lacks crucial context for a read 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 a single, efficient sentence with zero waste, front-loading the core purpose. It's appropriately sized for a simple tool, making it easy to parse quickly.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given no annotations and no output schema, the description is incomplete for a tool that likely returns structured status data. It fails to explain what 'status' entails (e.g., disruptions, operational state) or provide context on the API's behavior, leaving significant gaps for agent usage.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 100%, so the schema already documents both parameters (lineId and app_key). The description adds no additional meaning beyond what the schema provides, such as examples of line status outputs or API specifics, meeting the baseline for high coverage.

    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 verb ('Get') and resource ('status of a TfL line'), specifying it uses the Transport for London Unified API. However, it doesn't distinguish from sibling 'get_line_status_detail', leaving some ambiguity about scope differences.

    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?

    No guidance is provided on when to use this tool versus alternatives like 'get_line_status_detail' or 'plan_journey'. The description implies a simple status query but offers no explicit context or exclusions for usage.

    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 states the tool retrieves status and details but does not mention critical aspects like authentication requirements (implied by the optional 'app_key' parameter), rate limits, error handling, or the format of returned data. This leaves significant gaps in understanding the tool's 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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, 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.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the lack of annotations and output schema, the description is incomplete for effective tool use. It does not explain what 'status and details' entail, how results are structured, or any behavioral traits like authentication needs. For a tool with two parameters and no structured output information, this leaves the agent under-informed.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema description coverage is 100%, with clear descriptions for both parameters in the input schema. The description does not add any additional meaning beyond what the schema provides, such as examples of line IDs beyond 'victoria' or 'central', or details on when 'app_key' is required. This meets the baseline for adequate but not enhanced parameter semantics.

    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 verb ('Get') and resource ('status and details of a TfL line'), making the purpose specific and understandable. However, it does not explicitly differentiate from the sibling tool 'get_line_status', which likely provides similar functionality, leaving room for ambiguity in tool selection.

    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, such as the sibling 'get_line_status' or 'plan_journey'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage 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 but only states the basic function without details on rate limits, authentication needs, error handling, or what the response includes. It mentions using the TfL Journey Planner but doesn't explain behavioral traits like real-time data usage or potential costs.

    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 the core purpose without any wasted words. It directly communicates the tool's function in a clear and structured manner, making it easy to understand at a glance.

    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 (journey planning with 3 parameters) and no output schema, the description is minimally complete but lacks details on return values, error cases, or integration context. It covers the basic purpose but doesn't fully compensate for the absence of annotations or output schema, leaving gaps in understanding how to use it effectively.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema description coverage is 100%, so the input schema already documents all parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, but doesn't contradict it, meeting the baseline for high schema coverage.

    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 ('Plan journeys') and resource ('between two locations using the TfL Journey Planner'), with a precise verb that distinguishes it from sibling tools like get_line_status and get_line_status_detail, which focus on line status rather than journey planning.

    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 for its application. It lacks information about prerequisites, such as needing an app_key for certain API calls, or when not to use it, leaving usage entirely implicit.

    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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