Obenan Review Analyzer is an MCP server that enables AI assistants to ingest, store, and analyze customer feedback and product or service reviews. Designed for analysts, product managers, and customer success teams, this server acts as a structured bridge between raw feedback and language models. It organizes feedback items as discrete text resources using a custom URI scheme, allowing assistants like Claude to systematically track individual review entries. Users can log customer opinions, feature requests, or service complaints directly into the server using built-in tools. Once entries are accumulated, the server exposes dedicated prompt workflows that prompt the connected model to evaluate all recorded items and synthesize them according to customizable detail levels, such as brief summaries or detailed breakdowns. By integrating directly into local MCP environments, Obenan Review Analyzer simplifies sentiment extraction, trend identification, and customer insight reporting without requiring complex third-party infrastructure. The system maintains server state during active sessions, notifying client applications whenever new review notes are added or updated so that conversational agents always have current context.
Category: CRM, ERP & E-commerce
Tags: customer feedback, data analysis, reviews, sentiment analysis
To install and configure Obenan Review Analyzer for Claude Desktop, follow these steps: 1. Ensure you have uv installed on your system to run Python packages. 2. Open your Claude Desktop configuration file: - On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json - On Windows: %APPDATA%/Claude/claude_desktop_config.json 3. Add the server entry under the mcpServers object: json { "mcpServers": { "obenan-mcp-server": { "command": "uvx", "args": [ "obenan-mcp-server" ] } } } 4. Save the configuration file and restart Claude Desktop to load the tools and prompts.
Part of MCP Servers
Obenan Review Analyzer is a Model Context Protocol server designed for analyzing customer, product, and service feedback. It stores customer review entries as note resources and provides tools and prompts that help AI assistants synthesize user sentiment and recurring feedback themes.
The server provides the add-note tool to save review entries into a custom note resource scheme. It also exposes a summarize-notes prompt that aggregates stored reviews and directs your AI client to generate either brief or detailed analytical summaries.
The server works with any standard MCP client that supports stdio communication, tools, and prompts. It includes explicit setup instructions for Claude Desktop across macOS and Windows operating systems using the uvx package runner.
You can install and run the server using uvx by adding obenan-mcp-server to the mcpServers configuration object in your Claude Desktop configuration file, then restarting the client.