Hotel Ratings MCP Server Integration Guide
Section A: Quick Answer & Architectural Summary
The Hotel Ratings Model Context Protocol (MCP) integration bridges AI coding assistants to the Hotel Ratings security API. It exposes 1 validated endpoint operations as callable tools for Claude Desktop, Cursor, and VS Code. Configuration is managed via hosted registry at /config/amadeus-com-amadeus-hotel-ratings.json or local stdio bridge execution. Operates with zero authentication credentials out of the box. Operates exclusively in read-only query mode, safe for automated agent inspection loops.
MCPBridge Editorial Verdict: Hotel Ratings
AI coding workflows requiring programmatic access to Hotel Ratings (Security) endpoints
Low (1-2 mins)
Zero Authentication Required
Automated Spec Tracking
Claude Desktop, Cursor IDE, VS Code (Cline), Zed Editor
Read-only endpoints; safe query execution with zero mutation risk
MCPBridge rates Hotel Ratings as a standardized OpenAPI-to-MCP bridge providing structured tool definitions across 1 endpoints.
Technical Overview & Protocol Integration
The Hotel Ratings API, provided by Amadeus for Developers, offers programmatic access to aggregated hotel sentiment data and ratings derived from guest reviews. Its core capability is to retrieve the Hotel Sentiments for a given hotel, identified by its Amadeus property code. This endpoint, GET /e-reputation/hotel-sentiments, returns a structured score and detailed breakdown of feedback across multiple facets of the guest experience, such as service, facilities, room comfort, and value for money. The API is designed for enterprise-level applications within the travel and hospitality ecosystem, serving use cases for hotel chains analyzing brand performance, travel management companies assessing property quality for corporate bookings, online travel agencies (OTAs) enriching their listings with quality metrics, and travel intelligence platforms conducting market analysis. By providing normalized sentiment data from multiple review sources, it removes the need for developers to scrape, aggregate, and process disparate review platforms themselves.
Exposing this API as a tool via the Model Context Protocol (MCP) creates significant value for AI coding assistants by enabling them to serve as a direct interface to real-time hospitality intelligence. An AI agent, such as Claude Desktop or Cursor, can transform from a code generator into a dynamic data analyst and integration architect. Instead of a developer manually querying the API, writing parsing logic, and building visualization routines, they can instruct the AI to perform these complex, multi-step tasks. The model gains the ability to fetch live sentiment data, interpret the structured response, and use that information to drive subsequent actions in the codebase, such as populating a new field in a database schema, triggering an alert based on a low score, or generating a comparative report in code. This integration effectively embeds domain-specific knowledge and data retrieval capabilities directly into the developer's workflow.
Practical workflows enabled by this MCP server are numerous and context-aware. A developer could instruct the AI agent: "Query the Hotel Sentiments API for the Hilton Paris Opera (code: PARMILH) and then write a Python function that flags any aspect with a score below 7.0 for review." The AI would perform the API call, parse the sentiment facets, and generate the filtering logic. Another dynamic task could be: "Compare the sentiment scores for these two hotel property codes and create a markdown table summarizing the key differences in their 'service' and 'room_comfort' ratings." The agent would execute both API calls, analyze the data, and output the formatted comparison. For automation, a command like "Design a monitoring script that checks the overall sentiment score for this list of hotel codes daily and updates a JSON configuration file if any score drops by more than 15%," would showcase the AI's ability to scaffold complete operational tooling based on live API data.
Developers integrating this MCP server must adhere to critical security and configuration guidelines. While the API endpoint itself currently operates without traditional token-based authentication for this specific read-only sentiment endpoint, best practices still apply. The recommended access token generation via the Amadeus Authorization Guide should be followed if the endpoint's authentication requirements evolve or for other APIs in the portfolio. Access to the tool should be governed by the principle of least privilege, ensuring the AI assistant is only configured with permissions to query this specific endpoint and no others. Furthermore, developers must be aware that the test environment uses a subset of production data; therefore, validation of logic and data structures should be completed against the live environment before full deployment. All API calls from the AI agent should be logged for auditability, and any data handled must comply with data privacy regulations like GDPR, especially when incorporating user-specific booking information into queries.
By translating the OpenAPI 3.0 specification for Hotel Ratings into native Model Context Protocol (MCP) tool definitions, developers and AI agents gain programmatic access to endpoints over stdio or HTTP transports. Every endpoint is translated into a discrete tool payload complete with input argument validation, parameter descriptions, and return type definitions.
2. Technical Specifications Matrix
System Specifications
| API Name | Hotel Ratings |
| Slug Identifier | amadeus-com-amadeus-hotel-ratings |
| Category | Security |
| Auth Method | None Required |
| Endpoint Count | 1 tools mapped |
| Spec Version | OpenAPI v1.0.2 |
| Transport Type | STDIO |
| Publisher Source | auto |
Developer Resources
3. Multi-Client Installation Matrix
Copy and paste these pre-formatted JSON snippets into your MCP client configuration files.
Claude Desktop
Add to claude_desktop_config.json
{
"mcpServers": {
"amadeus-com-amadeus-hotel-ratings": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-openapi",
"https://api.apis.guru/v2/specs/amadeus.com/amadeus-hotel-ratings/1.0.2/swagger.json"
],
"env": {
"HOTEL_RATINGS_API_KEY": "your_hotel_ratings_api_key"
}
}
}
}Cursor IDE
Settings → MCP Servers → Add Hosted Config
{
"mcpServers": {
"amadeus-com-amadeus-hotel-ratings": {
"url": "https://mcpbridge.org/config/amadeus-com-amadeus-hotel-ratings.json"
}
}
}Saves as .cursor/mcp.json in the download. Move it to your project root.
VS Code / Cline
Use with MCP extension config
{
"mcpServers": {
"amadeus-com-amadeus-hotel-ratings": {
"url": "https://mcpbridge.org/config/amadeus-com-amadeus-hotel-ratings.json"
}
}
}4. Security Architecture & Credentials Reference
Key parameters and credential variable mappings for Hotel Ratings.
Security Considerations & Sandbox Guidance: Hotel Ratings
Authorization credential isolation, least privilege boundaries, and container sandboxing options.
None Required
Read-Only Operations
Local MCP bridge process making outbound HTTPS requests to upstream API
Isolation & Principle of Least Privilege
Ensure outbound network access to the API endpoint is permitted. Use restricted API tokens with minimal read/write scopes.
Actionable Operational Guidelines
- Verify network firewall rules allow outbound traffic to upstream API endpoints.
- Read-only operations ensure that automated agent loops cannot alter or delete remote data.
- Apply token rate limits and monitor usage in your provider dashboard to prevent unexpected quota consumption.
| Variable Name | Required | Example Value |
|---|---|---|
| HOTEL_RATINGS_API_KEY | REQUIRED | your_hotel_ratings_api_key |
5. Endpoints & Tool Schemas Matrix
Search and inspect the 1 tool signatures mapped from OpenAPI.
Executable Code Integration Examples
Call Hotel Ratings endpoints via cURL, TypeScript, or Python REST SDKs.
curl -X GET "https://api.apis.guru/v2/specs/amadeus.com/amadeus-hotel-ratings/1.0.2/swagger.json/e-reputation/hotel-sentiments" \ -H "Content-Type: application/json" \ # No auth required
Concrete Real-World Use Cases for Hotel Ratings
Practical multi-step agentic workflows and prompt directives demonstrating concrete developer outcomes.
Automated Contextual Workflow Integration
Practical workflows enabled by this MCP server are numerous and context-aware. A developer could instruct the AI agent: "Query the Hotel Sentiments API for the Hilton Paris Opera (code: PARMILH) and then write a Python function that flags any aspect with a score below 7.0 for review." The AI would perform the API call, parse the sentiment facets, and generate the filtering logic. Another dynamic task could be: "Compare the sentiment scores for these two hotel property codes and create a markdown table summarizing the key differences in their 'service' and 'room_comfort' ratings." The agent would execute both API calls, analyze the data, and output the formatted comparison. For automation, a command like "Design a monitoring script that checks the overall sentiment score for this list of hotel codes daily and updates a JSON configuration file if any score drops by more than 15%," would showcase the AI's ability to scaffold complete operational tooling based on live API data.
- AI assistant inspects prompt context and selects relevant tool
- Validates parameter payload against OpenAPI JSON Schema
- Executes tool call and formats structured API response
Data Inspection & Resource Querying
Query Hotel Ratings resources such as "/e-reputation/hotel-sentiments" to retrieve contextual data directly during coding sessions.
- Agent selects /e-reputation/hotel-sentiments tool
- Passes search filters or resource identifiers
- Renders JSON payload in chat context for developer review
Good Fit vs. Poor Fit Criteria for Hotel Ratings
Architectural guidelines to determine when to adopt this integration and when to explore alternatives.
When to Choose / Good Fit
- AI coding assistants in Claude Desktop or Cursor requiring structured tool access to Hotel Ratings.
- Developers who want standardized OpenAPI-to-MCP translation without building custom server code.
- Workflows that benefit from automated parameter validation against official OpenAPI 3.0 schemas.
- Teams seeking zero-maintenance hosted JSON configurations for easy distribution.
When to Avoid / Poor Fit
- Ultra-high frequency data ingestion exceeding typical LLM context windows and token rate limits.
- Unattended autonomous agent loops with write access where human approval of mutations is mandatory.
- Environments lacking outbound internet access to upstream Hotel Ratings API servers.
Verification & Evidence Audit: Hotel Ratings
OpenAPI 3.0 specification parsed and validated via automated build pipeline.
Independent Evidence Checks
Valid specification version 1.0.2 with 1 endpoints indexed.
No authentication required.
JSON Schemas mapped to MCP tools/call standard format.
Automated schema validation only; live upstream API calls require developer credentials.
Project Health & Maintenance Audit: Hotel Ratings
ActiveActivity & Cadence
Transparent Quality Score Breakdown
Alternatives & Comparison Table (Security)
Comparative trade-offs between Hotel Ratings and similar ecosystem tools in the Security category.
| Option | Best For | Main Difference vs. Hotel Ratings | Setup / Runtime | Explore |
|---|---|---|---|---|
| 1Password Connect | Developers needing Security operations with 10 tools | 10 endpoints vs 1 endpoints | auto / v1.5.7 | View → |
| Adyen Balance Control API | Developers needing Security operations with 1 tools | 1 endpoints vs 1 endpoints | auto / v1 | View → |
| Agricultural Scientists Recruitment Board | Developers needing Security operations with 1 tools | 1 endpoints vs 1 endpoints | auto / v3.0.0 | View → |
9. Error Resolution & Troubleshooting Guide
Contextual diagnostics for HTTP status codes and JSON-RPC tool bridge operations.
-32600 (Invalid Request)Root Cause: Malformed JSON-RPC payload sent to local MCP bridge process.
Resolution Action: Verify MCP client payload adheres to JSON-RPC 2.0 specification.
-32601 (Method Not Found)Root Cause: Requested operation does not exist in mapped Hotel Ratings OpenAPI endpoint schemas.
Resolution Action: Inspect Section 5 endpoints table to confirm valid method names and paths.
-32602 (Invalid Params)Root Cause: Missing or invalid parameters for target tool operation.
Resolution Action: Check parameter data types against OpenAPI JSON Schema specification.
429 Rate Limit ExceededRoot Cause: Upstream Hotel Ratings API request rate limit quota reached.
Resolution Action: Implement exponential backoff in tool execution loop or verify provider plan quotas.
OPENAPI_GATEWAY_TIMEOUTRoot Cause: Upstream Hotel Ratings endpoint response latency exceeded timeout threshold.
Resolution Action: Verify network connectivity and check provider system status dashboard.
Official Verified Sources for Hotel Ratings
Authoritative upstream repositories, specifications, package registries, and configuration endpoints.
OpenAPI 3.0 Specification
Machine-readable OpenAPI schema source used for MCP tool mapping.
https://api.apis.guru/v2/specs/amadeus.com/amadeus-hotel-ratings/1.0.2/swagger.jsonHosted MCPBridge Configuration
Pre-generated Model Context Protocol JSON configuration hosted on MCPBridge.
https://mcpbridge.org/config/amadeus-com-amadeus-hotel-ratings.jsonOpenAPI-to-MCP Converter Tool
Client-side browser converter to customize or filter endpoint tools.
https://mcpbridge.org/convert/Claim & Maintainer Verification
Submit a claim to verify API publisher ownership and update metadata.
https://github.com/stormlive-ai/mcp-bridge-docs/issues/new?title=Claim+Listing%3A+Hotel+Ratings+%28api%3A+amadeus-com-amadeus-hotel-ratings%29&labels=claim-listing&body=%23%23+Claim+Listing+Request%0A%0AI+would+like+to+claim+this+listing%3A%0A%0A-+**Type%3A**+api%0A-+**ID%3A**+amadeus-com-amadeus-hotel-ratings%0A-+**Name%3A**+Hotel+Ratings%0A%0A%23%23%23+Your+Information%0A%0A**GitHub+Handle%3A**+%3C%21--+your+GitHub+username+--%3E%0A%0A**Email%3A**+%3C%21--+optional%2C+for+verification+--%3E%0A%0A**Relationship+to+this+API%3A**%0A-+%5B+%5D+I+am+the+API+provider+%2F+maintainer%0A-+%5B+%5D+I+am+an+authorized+representative%0A-+%5B+%5D+Other%3A%0A%0A%23%23%23+Verification+Method%0A-+%5B+%5D+I+will+add+a+CNAME%2FTXT+record+to+verify+domain+ownership%0A-+%5B+%5D+I+can+confirm+from+an+email+address+at+the+provider+domain%0A-+%5B+%5D+I+maintain+the+GitHub+repository%0A%0A%23%23%23+Updates+I%27d+Like+to+Make+%28optional%29%0A%3C%21--+What+would+you+like+to+update%3F+Description%2C+links%2C+category%2C+etc.+--%3E%0A%0A---%0A*Submitted+via+MCP-Bridge+claim+form*Frequently Asked Technical Questions: Hotel Ratings
Targeted developer questions regarding installation, client configuration, credentials, and error resolution.
The Hotel Ratings MCP server connects AI coding assistants (Claude Desktop, Cursor, VS Code, Zed) to the Hotel Ratings API using the Model Context Protocol. It converts 1 OpenAPI operations into native MCP tools callable during chat sessions.