Skip to main content
Glama
him229

stays

by him229
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool has a distinct purpose: search_hotels for fast listing, get_hotel_details for deep single-hotel info, and search_hotels_with_details for multi-hotel comparison. No overlaps.

    Naming Consistency5/5

    All tools follow a consistent verb_noun snake_case pattern: get_hotel_details, search_hotels, search_hotels_with_details. Naming is predictable.

    Tool Count5/5

    With 3 tools covering search, detail retrieval, and combined search+details, the count is well-scoped for a hotel information server.

    Completeness4/5

    The tools cover the core workflows: finding hotels, getting details, and comparing. Minor gap: no filtering or sorting parameters beyond what's described, but the search tools include common filters.

  • Average 4.6/5 across 3 of 3 tools scored.

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

    • 2 of 3 community issues answered or closed in the last 6 months
    • 2 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 failing

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

  • Add related servers to improve discoverability.

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 already declare readOnlyHint and idempotentHint, so description adds context about being a single RPC that returns rooms, rate plans, and cancellation policies, enhancing transparency without contradicting 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?

    Three focused sentences front-load key information (deep detail for one hotel, required prerequisite, return contents) with no unnecessary words, earning its keep.

    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 presence of an output schema, description adequately covers inputs, prerequisites, return value categories, and sibling alternatives, leaving no critical gaps for an agent to misuse the tool.

    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 has 0% description coverage, so description must compensate. It implies entity_key is the hotel identifier, check_in/check_out for dates, and currency for currency, but does not detail format or constraints per parameter, offering only moderate semantic value.

    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 retrieves deep detail for ONE hotel using entity_key from search_hotels, and distinguishes itself from sibling tools by explicitly naming search_hotels_with_details for multi-hotel comparisons.

    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?

    It explicitly notes the prerequisite of entity_key from search_hotels and provides an alternative tool (search_hotels_with_details) for multi-hotel deep comparison, guiding proper tool selection.

    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 and idempotentHint=true. The description adds that it is a 'Fast list-view' search, 'One RPC', and explains that entity_key values feed into get_hotel_details, providing context beyond the 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 front-loaded with key guidance ('USE THIS FIRST'), then lists return fields and filter triggers in an efficient bullet list. Slightly verbose but well-structured with no wasted sentences.

    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?

    With 19 parameters and an output schema present, the description covers all necessary context: return fields, entity_key usage, filter mapping, and relationship to sibling tools. Complete for a search tool.

    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%, and the description adds a 'Common filter triggers' section that maps natural language requests (e.g., 'free cancellation' → free_cancellation=True) to specific parameters, providing semantic guidance beyond the 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 'Fast list-view hotel search' and instructs 'USE THIS FIRST to discover hotels', distinguishing it from siblings by naming search_hotels_with_details and explaining entity_key as input to get_hotel_details.

    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 says 'USE THIS FIRST' and 'Prefer this over search_hotels_with_details unless the user explicitly asks for room/rate/cancellation detail', providing clear when-to-use and when-not-to guidance with the sibling tool named.

    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?

    Annotations already declare readOnlyHint=true and idempotentHint=true. Description adds that it performs parallel detail fetch (multiple RPCs) and imposes a hard cap of 15 on max_hotels, providing transparent 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 gives usage guidance and constraints. Extremely concise and front-loaded; no wasted words.

    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?

    Despite high complexity (19 parameters, sibling tools), the description covers purpose, usage context, cost, and hard cap. Output schema exists but does not need description. Complete enough for an agent to decide when and how to use.

    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?

    With schema description coverage at only 5%, the description compensates slightly by mentioning max_hotels cap and default, but does not explain the many other parameters. However, the tool's purpose is clear and many parameters are standard, so a baseline of 3 is appropriate.

    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 combines search with parallel detail fetch for top N hotels. It distinguishes itself from siblings 'search_hotels' (likely just search) and 'get_hotel_details' (single hotel) by explicitly mentioning the combined functionality.

    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 states when to use: when user wants to compare rooms, rates, or cancellation policies across multiple hotels. Also warns about cost (1 + N RPCs) and hard cap on max_hotels, guiding appropriate usage.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

stays MCP server

Copy to your README.md:

Score Badge

stays MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/him229/stays'

If you have feedback or need assistance with the MCP directory API, please join our Discord server