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urbanis

street-generator-mcp

by urbanis
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a unique purpose: build_share_url creates a sharing link, import_street_from_osm fetches real-world data, and render_street visualizes a config. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case: build_share_url, import_street_from_osm, render_street.

    Tool Count4/5

    With only 3 tools, the set is slightly minimal but covers the core workflow of import, render, and share for street generation. The count is reasonable for a focused domain.

    Completeness3/5

    The tools cover import, render, and share, but lack any editing or querying capabilities for generated configurations. The user must rely on Claude to produce the StreetConfig, which may be a gap for manual adjustments.

  • Average 3.8/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 24 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

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  • 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. It only states the output is a link, but does not disclose any side effects, authorization needs, or other behavioral traits beyond what is minimally inferred.

    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, front-loaded sentence with no extraneous information. Every word serves a purpose.

    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?

    The description adequately states the tool's function but does not specify the exact format of the return link, mention validation, or address potential limitations. Given the complexity of the input (nested object) and lack of output schema, more detail would be beneficial.

    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 input schema defines the 'config' parameter with nested structure, but schema description coverage is 0% (no descriptions in schema for top-level config). The description adds no additional meaning about the parameter beyond what the schema provides.

    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 explicitly states the verb 'return' and the resource 'streetgenerator.com link', and specifies that it opens the StreetConfig in the live app. This clearly differentiates it from sibling tools like import_street_from_osm and render_street.

    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 generating share links, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it.

    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?

    With no annotations, the description carries full burden. It states the tool renders deterministically, suggesting a read-only, pure output operation. However, it lacks explicit statements about side effects, idempotency, or resource usage, which would improve transparency.

    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 two sentences, front-loaded with purpose, and contains no wasted words. It efficiently conveys the tool's role and context.

    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 complexity (nested parameters, no output schema, no annotations), the description is too brief. It omits return value format (e.g., SVG URL or data), prerequisites, and details about the 'Street Generator visual style', leaving the agent with insufficient guidance.

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

    Parameters2/5

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

    Schema description coverage is 0%, so the description must compensate. It does not explain any parameters or their meanings beyond what the schema structure provides. The complex nested schema (e.g., config, style) is left for the agent to interpret without added guidance.

    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 it renders a StreetConfig as an illustrated SVG cross-section, specifying included elements (people, cars, trees). It also distinguishes from sibling tools (build_share_url and import_street_from_osm) by noting this tool draws the config deterministically in a visual style.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides context by stating that Claude produces the StreetConfig and this tool draws it, implying use after obtaining a config. However, it does not explicitly state when not to use this tool or mention alternatives to siblings, leaving some ambiguity.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Without annotations, the description carries full burden. It discloses the two-step flow, disambiguation with lettered candidates, and that lat/lng skips geocoding. However, it does not mention error handling (e.g., address not found) or the output format, which would improve transparency.

    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 three sentences, front-loaded with the purpose, then requirements, then the disambiguation process. Every sentence adds critical information without redundancy.

    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?

    Despite covering the input and flow well, the description does not specify the output of the tool (e.g., image, data model). Since there is no output schema, this omission reduces completeness. The style parameter defaults are in the schema but not summarized.

    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?

    Schema coverage is high (88%), so baseline is 3. The description adds value by explaining the special role of lat/lng in the disambiguation flow and emphasizing completeness of address parameters. Style parameters are not mentioned but are covered in schema 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 tool renders a real street cross-section by reading from OpenStreetMap, specifying the required complete address. It effectively distinguishes from sibling tools by detailing the unique two-step process involving address input and optional lat/lng for disambiguation.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit guidance on when to use the tool (complete address required) and when to ask the user for missing parts or present candidates. It explains the disambiguation flow but does not compare this tool to its siblings (build_share_url, render_street), reducing its helpfulness for alternative selection.

    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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