Agoda Review MCP Server

The Agoda Review MCP server is a lightweight service that exposes hotel‑review data from Agoda to large language models via the Model Context Protocol. By aggregating both positive and negative reviews for a given property, it gives an AI assistant the ability to provide balanced, evidence‑based recommendations. This solves a common pain point for travel‑related applications: pulling trustworthy sentiment data from a third‑party source and presenting it in a format that an LLM can easily consume.

The server runs on Java 17+ and bundles a small REST interface that the MCP client can query. When an LLM asks for “reviews of Hotel X in Bali,” the server performs a lookup against Agoda’s public review feed, stitches together the most relevant comments, and returns them as structured JSON. The LLM can then reference these reviews in its response or feed them into downstream prompts for sentiment analysis, summary generation, or personalized suggestions. Because the data is delivered in a uniform schema, developers can quickly integrate it into existing Claude workflows without writing custom parsers.

Key capabilities include:

• Dual‑sentiment aggregation – the server automatically pulls both positive and negative reviews, giving a holistic view of user experience.
• Search‑by‑hotel – query by hotel name, ID, or location to retrieve the latest reviews.
• Structured output – each review is returned with rating, author, date, and full text, ready for NLP pipelines.
• Stateless design – no persistent storage is required; the server fetches fresh data on each request, ensuring up‑to‑date insights.

Typical use cases are plentiful for travel‑tech and hospitality products:

• Travel agents can embed real reviews in chatbots, helping clients decide on accommodations.
• Recommendation engines may weight user preferences by the sentiment score extracted from these reviews.
• Customer‑feedback analytics teams can ingest review data into dashboards or train models for sentiment classification.
• Content creators might generate concise hotel summaries or highlight unique guest experiences.

Integrating the Agoda Review MCP into an AI workflow is straightforward: a developer configures the server in the Claude MCP setup, then invokes it via the standard or calls. The LLM can ask for a review list, receive the JSON payload, and immediately use it to craft nuanced responses or trigger further processing steps. The server’s lightweight nature means it can run locally, in a container, or on a cloud function, giving teams flexibility around latency and cost.

In short, the Agoda Review MCP bridges the gap between raw hotel‑review data and conversational AI. By delivering balanced, up‑to‑date insights in a machine‑friendly format, it empowers developers to build richer, more trustworthy travel experiences without the overhead of scraping or parsing Agoda’s website themselves.