Lodging Decision
Server Details
Agent-facing lodging decision tool. Non-sensitive categories only. Alpha, unauthenticated.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.4/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion or misselection. The tool's purpose is clear and distinct.
The single tool name uses a clear snake_case format and is self-descriptive. There are no other tools to create inconsistency.
One tool feels thin for a server; the functionality is broad but could logically be split into separate concerns (e.g., scoring, risk assessment). It is borderline but not unreasonable.
For its stated purpose of ranking lodging candidates and providing evidence-backed recommendations, the tool covers all necessary aspects: scoring, tradeoffs, risk flags, and missing information. It explicitly excludes search and booking, which are outside its scope.
Available Tools
1 toollodging_decisionLodging DecisionAInspect
Ranks caller-supplied lodging candidates for a traveler/trip and returns a deterministic, evidence-backed recommendation with score breakdown, tradeoffs, risk flags, missing information, and confidence.
SCOPE (alpha, non-sensitive categories only): budget, location, amenities, quality/reviews, cancellation policy, fees, remote-work and family and business/relocation/event trip framing, and stated accessibility needs. This tool does NOT accept, infer, or act on race, color, national origin, religion, sex, gender identity, sexual orientation, familial status, or any other protected characteristic or Safety & Belonging signal -- requests containing such content in free-text fields are rejected, not silently filtered.
This tool does not search inventory (you must supply candidate_listings), does not book or transact, and does not persist any data. It is unauthenticated, unversioned, alpha-quality: recommendations are deterministic given identical input but are not calibrated against real human booking outcomes. Always re-verify availability, price, and policy before booking.
| Name | Required | Description | Default |
|---|---|---|---|
| trip | Yes | ||
| traveler | Yes | ||
| candidate_listings | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description compensates thoroughly: it discloses deterministic behavior, rejection of protected-characteristic content, no persistence, alpha quality, and unauthenticated operation. It also details the output components.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description opens with a crisp summary of what the tool does, then layers scope, exclusions, and caveats in a logical order. No wasted words; each sentence conveys necessary context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers functionality, scope, exclusions, output components, and limitations. Given the complex nested schema and lack of annotations, it provides sufficient context for an agent to decide when to call the tool and what to expect, though it could be more explicit about error handling or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description carries the burden. It clarifies that candidate_listings are caller-supplied and outlines the decision scope (budget, location, amenities, etc.), but does not detail the meaning or constraints of individual parameters beyond what their names imply in the schema. Partial compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool ranks caller-supplied lodging candidates and returns a deterministic, evidence-backed recommendation with score breakdown, tradeoffs, risk flags, missing information, and confidence. It explicitly distinguishes itself from search, booking, and persistence tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the tool does not search inventory, book, or persist data, making clear the user must supply candidate_listings. It also sets expectations for alpha quality and verification before booking, though it doesn't name alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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