A
licenseNot graded
qualityB
maintenanceBook hotels worldwide — search, price, prebook & book across 249 countries. 65 tools for hotel search, flights, loyalty, analytics. Zero API keys needed. at best prices for hotels 3 M+ property
22
1
MIT
Got Cosy
Server Details
Travel/hotel data: 6,300 hotels scored for cosiness from guest reviews; verified booking links.
If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
2 toolsfind_cosy_hotelsAInspect
Find live, cosy-scored hotels from Got Cosy's cosiness index (gotcosy.com): hotels scored 0-10 for warmth, intimacy and character from photos and reviews. Only returns hotels that clear the public floor (score 5.0+). Optionally filter by city, country and a minimum cosy score.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | City name, e.g. "Paris" | |
| limit | No | Max results (default 20, max 100) | |
| country | No | Country name, e.g. "France" | |
| min_score | No | Minimum cosy score 0-10 (the public floor is 5.0 regardless of this value) |
TDQS
A4.1/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that only hotels with score >=5.0 are returned, that min_score does not override the floor, and that data is 'live'. This provides important behavioral context beyond basic purpose.
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 concise sentences: first states main purpose and source, second lists optional filters. No wasted words, information is front-loaded.
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 no output schema, the description does not specify what fields are returned for each hotel (e.g., name, location, score). While sufficient for a search tool, it lacks details about the result 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?
Schema coverage is 100%, but the description adds value by explaining the min_score parameter's interaction with the public floor ('the public floor is 5.0 regardless of this value'). This clarifies semantics beyond the schema's 'Minimum cosy score'.
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 finds 'live, cosy-scored hotels' from a specific source, with a defined score range (0-10) and a floor of 5.0. It distinguishes itself from sibling tool 'get_hotel_feeling' by focusing on listing hotels rather than retrieving a single hotel's feeling.
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 searching hotels with optional filters but does not explicitly compare to sibling tool 'get_hotel_feeling' or specify when to use each. It mentions the public floor but lacks when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_hotel_feelingAInspect
Get one hotel's cosy score, evidence signals and description from Got Cosy, by its slug (as returned in find_cosy_hotels' results, or from a gotcosy.com/en/hotels/ URL). Below-floor hotels return {below_bar:true} with no score exposed.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The hotel's Got Cosy slug |
TDQS
A4.8/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses special behavior for below-floor hotels. No annotations provided, so description carries burden. Could mention authentication or rate limits, but fine for a simple 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?
Two sentences, no fluff. Front-loaded with purpose. Efficient and well-structured.
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?
No output schema, but description adequately covers return values (score, signals, description) and edge case. Complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described. Description adds value by explaining how to obtain the slug from find_cosy_hotels results or URL, beyond the schema's brief description.
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?
Clearly states verb 'get', resource 'one hotel's cosy score, evidence signals and description', and input 'slug'. Distinguishes from sibling tool 'find_cosy_hotels' by specifying slug source.
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 mentions when to use (by slug from find_cosy_hotels or URL) and describes edge case (below-floor hotels return {below_bar:true}). Provides clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
- First observed
find_cosy_hotels - First observed
get_hotel_feeling
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TDQS
A4.4/5.0
Disambiguation5/5
Each tool targets a distinct operation: searching for hotels vs. retrieving details for a specific hotel. No overlap in functionality.
Naming Consistency5/5
Both tools follow a consistent verb_noun pattern: 'find_cosy_hotels' and 'get_hotel_feeling'. While 'find' and 'get' are different, they are both common action verbs and the pattern is uniform.
Tool Count4/5
With only 2 tools, the set is minimal but appropriate for a niche service focused on accessing a cosiness index. It covers the core needs of searching and retrieving details without unnecessary bloat.
Completeness5/5
The tool set provides all necessary operations for the domain: searching with filters and retrieving detailed information by identifier. No obvious gaps as the service is read-only and focused on a single entity type.