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jasp-nerd

kamernet-mcp

by jasp-nerd
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

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 has a clearly distinct purpose: search_listings for finding listings, get_listing for details of a specific listing, and get_new_listings for monitoring new listings. There is no overlap or ambiguity.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern with camelCase (get_listing, get_new_listings, search_listings). The naming is predictable and easy to understand.

    Tool Count5/5

    With 3 tools, the server is well-scoped for its purpose of browsing and monitoring rental listings. Each tool is necessary and none are extraneous.

    Completeness4/5

    The tool set covers search, detail retrieval, and monitoring new listings, which are the core operations for a listing viewer. A minor gap is the lack of a separate tool for listing available cities or filter options, but search_listings likely handles filters adequately.

  • Average 4.4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 8 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 MIT License.

  • 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.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}

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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

  • Behavior4/5

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

    Annotations declare readOnlyHint (safe read) and openWorldHint (unexpected fields possible). Description adds specific included fields (descriptions in both languages, rent, deposit, energy label, registration, landlord stats, photo URLs), providing clear behavioral context beyond annotations.

    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: first states purpose, second lists what's included. No extraneous text, front-loaded with key action. Highly efficient.

    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 output schema exists (handles return values) and annotations provide safety info, description adequately covers tool function and output contents. Lacks error handling details but is sufficient for a simple read operation.

    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 already fully covers the 'listing' parameter with format and source. Description adds no new semantic information beyond restating the parameter's purpose, so baseline 3 applies.

    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?

    Clear verb 'Get' and specific resource 'full details of one Kamernet listing'. Distinguishes from siblings: search_listings returns multiple, get_new_listings returns new listings.

    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?

    Specifies input format and origin (URL from search_listings). Lists included details. Implicit use case for single listing retrieval, but no explicit when-not or alternative guidance.

    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 indicate readOnlyHint=true and openWorldHint=true. The description adds behavioral traits: returns one page of summaries, includes specific fields, and notes that sponsored ads may not match all filters. This exceeds what annotations provide without contradiction.

    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 concise with four sentences, each adding essential information. It front-loads the purpose and resource, then details returns, directs to a sibling tool, and clarifies a special case. No superfluous content.

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

    Completeness5/5

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

    Given the full schema coverage, annotations, and presence of an output schema, the description provides sufficient context. It explains core functionality, return fields, and a special behavior (sponsored ads), making the tool easy to use correctly.

    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 100% with descriptions for each parameter. The description adds meaning by stating that price is in euros/month and surface in m², and explains how sponsored ads behave, which aids in understanding the output beyond the raw schema.

    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 verb 'search' and the resource 'rental listings on Kamernet.nl'. It specifies what is returned (price, surface, availability, URL) and distinguishes from the sibling tool get_listing by instructing to use it for full details.

    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 explains that for full listing details one should use get_listing, and notes that sponsored top ads are returned separately. While it does not explicitly state when not to use this tool or mention get_new_listings, it provides useful context for selecting between tools.

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

  • Behavior5/5

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

    Discloses sorting by newest, client-side filtering, statelessness, and politeness constraints. Annotations already indicate readOnly and openWorld, and description adds valuable behavioral context beyond those.

    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?

    Four sentences, all essential. First sentence states purpose, subsequent sentences add guidance and detail. No wasted words.

    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?

    Description covers the core use case well. Annotations confirm safety and open-world nature, and output schema exists. Minor gaps: no mention of optional filters like max_rent, but overall adequate.

    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 coverage is 50% with descriptions for 3 of 6 parameters (city, since, radius_km). The description does not add further parameter details, so it meets a baseline but does not compensate for missing 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 checks for new listings since a given timestamp for stateless monitoring. It distinguishes from siblings (get_listing, search_listings) by focusing on incremental updates.

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

    Usage Guidelines5/5

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

    Explicitly advises polling periodically, remembering the timestamp, and not polling more than every few minutes. Provides clear usage context without needing to reference alternatives.

    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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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.

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