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malkreide

swiss-housing-mcp

by malkreide

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct aspect: listing dwellings, historical construction, pipeline, code explanation, and cache status. There is no overlap or ambiguity in their purposes.

    Naming Consistency3/5

    Tool names mix patterns: verb_noun (lookup_dwellings, explain_code), adjective_noun (new_construction), and noun_noun (construction_pipeline, dump_status). While readable, the lack of a uniform pattern reduces consistency.

    Tool Count5/5

    Five tools is well-scoped for a niche domain like Swiss housing data. Each tool serves a clear function without excess or deficiency.

    Completeness4/5

    The tools cover current dwelling data, historical construction, future pipeline, code decoding, and system status. A minor gap is the lack of a dedicated building-level query beyond dwellings, but the set supports the stated planning use case.

  • Average 3.5/5 across 5 of 5 tools scored.

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

    • No community issues in the last 6 months
    • 11 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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

  • Behavior3/5

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

    Annotations already indicate readOnlyHint=true. Description adds context about the 4+ room share being a proxy for family housing, but does not disclose any additional behavioral traits such as data source, update frequency, or limitations.

    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?

    Description is two sentences, efficiently conveying core purpose and a key interpretation note. No redundancy or fluff.

    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?

    With an output schema present, return value explanation is not needed. However, the description lacks usage context and does not fully cover parameters. Adequate but with gaps.

    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%. Description only explains municipality_bfs with an example. Parameters canton and since_year are not described at all, leaving their semantics unclear.

    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?

    Description clearly states it returns annual new residential construction data for a municipality, including buildings, dwellings, and 4+ room dwellings. However, phrasing 'existing buildings' may cause confusion about whether it covers new construction or existing stock.

    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 on when to use this tool versus siblings like lookup_dwellings or construction_pipeline. Does not mention alternatives 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?

    Annotations already declare readOnlyHint=true, so the description's additional information about status breakdowns and the interpretation of 'under construction' as an early indicator adds useful behavioral context. However, it does not disclose potential limitations like data availability by municipality or time-range constraints.

    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 concise sentences: the first states the core purpose, the second details the status categories, and the third explains the practical implication. Every sentence adds value, and the content is front-loaded with the most critical information.

    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 presence of an output schema and the tool's moderate complexity, the description covers the data meaning and use case. However, it omits parameter semantics and does not specify what the output contains or how to interpret the status codes fully (though codes are listed). The description is adequate but not comprehensive.

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

    Parameters1/5

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

    The input schema has 0% description coverage for its two parameters (canton, municipality_bfs). The description does not mention these parameters or provide any guidance on their values, formats, or roles. With no schema descriptions and no parameter information in the description, the agent receives no help beyond the schema structure.

    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 specifies the tool retrieves buildings and dwellings in the planning/construction pipeline of a municipality, with explicit breakdowns by status codes. This verb-resource combination is distinct from sibling tools like lookup_dwellings (likely existing dwelling data) and new_construction (new building registrations). The context of early indicator for school-space planning further differentiates its use case.

    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 getting pipeline data for a municipality and hints at its value for school-space planning, but it does not explicitly state when to prefer this tool over siblings or when not to use it. No exclusions or alternative recommendations are provided.

    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?

    Annotations already declare readOnlyHint=true. The description adds context (data source 'daily cantonal dump' and included fields) but does not disclose behavior beyond that, such as error handling or permissions. No contradiction with annotations.

    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 concise (two sentences) and front-loaded with the core action. However, it could be slightly more structured with bullet points for clarity.

    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?

    For a read-only list tool with an output schema, the description adequately mentions included fields but omits explanation of the required 'egid' parameter and the default value for 'canton'. The data source reference is vague.

    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 should explain parameters. However, it does not mention 'egid' as building ID or 'canton''s role. It only references 'a building' implicitly, leaving parameter semantics unclear.

    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 function: 'List all dwellings (EWID) of a building' and specifies included attributes (rooms, floor area, floor, status). This distinguishes it from sibling tools like new_construction or dump_status.

    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?

    Usage is implied but not explicit. The description does not mention when to use this tool versus alternatives, nor does it provide conditions for appropriate use.

    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?

    Annotations already declare readOnlyHint=true, so the read-only nature is clear. The description adds value by specifying the source of the labels (official code table) and the supported languages (DE/FR/IT), going beyond what annotations provide.

    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 very concise at two sentences, but the second sentence could be more structured or broken into bullet points for clarity. No superfluous information, but room for slight improvement.

    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 (3 params, no enums) and the presence of an output schema, the description adequately covers the main purpose. However, it lacks explanation for the optional parameter and does not mention the output schema's structure, resulting in moderate completeness.

    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?

    With 0% schema description coverage, the description bears the full burden of explaining parameters. It includes an example of 'attribute' and 'code' but does not describe the optional 'canton' parameter at all, leaving a gap in understanding.

    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 decodes GWR code values into human-readable labels, with a specific verb and resource. It provides an example of inputs (GSTAT=1004) and distinguishes itself from sibling tools that handle different tasks.

    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 use for decoding codes from a specific code table, but does not explicitly state when to use this tool vs alternatives, nor does it mention any prerequisites or when not to use it. Sibling tools have different purposes, so some implicit differentiation exists.

    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?

    Annotations already declare readOnlyHint=true. The description adds value by stating the tool never returns empty records and reports last refresh time, which is beyond what annotations provide. No contradictions.

    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?

    Two sentences, no wasted words. The key information is front-loaded and every sentence contributes meaning.

    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 zero parameters and the existence of an output schema, the description adequately covers the tool's behavior and return value. It is sufficient for the agent to understand what to expect, though it doesn't detail the output structure.

    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?

    No parameters exist, so the baseline is 4. The description correctly adds no parameter information since none are needed.

    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 shows cache status of GWR dumps with graceful degradation. It is distinct from sibling tools like lookup_dwellings which retrieve data. No explicit differentiation from siblings, but the purpose is clear.

    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 checking cache health even when sources are unreachable, but does not explicitly state when to use it over alternatives. It provides context but no exclusions or direct guidance.

    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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