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OpenReplay Session Analysis MCP Server

@rsp2k

基本信息

分类

其他

许可证

MIT license

传输方式

stdio

作者

rsp2k

关于 OpenReplay Session Analysis MCP Server

A Model Context Protocol (MCP) server for analyzing OpenReplay session recordings and user behavior patterns

#openreplay#session-analysis#user-behavior

OpenReplay Session Analysis MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "openreplay-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

OpenReplay Session Analysis MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is OpenReplay Session Analysis MCP Server?

An MCP server that enables AI assistants to analyze OpenReplay session recordings and user behavior patterns. It searches, filters, and provides actionable insights from OpenReplay data, helping developers and UX researchers detect problems and understand user journeys.

How to use OpenReplay Session Analysis MCP Server?

Install by cloning the repository, creating a Python virtual environment, and installing dependencies. Configure OpenReplay API credentials in a .env file (API key, project ID, API URL). Run the server with python run_server.py or via Docker. Connect to an MCP client like Claude Desktop by adding the server to claude_desktop_config.json.

Key features of OpenReplay Session Analysis MCP Server

  • Session search and filtering by date, user, errors, duration
  • User journey analysis with page flow mapping
  • Problem detection: rage clicks, form abandonment, errors
  • AI-powered session summaries and insights
  • User behavior analysis across multiple sessions
  • Similar session finding for comparable issues

Use cases of OpenReplay Session Analysis MCP Server

  • Debugging: find recent error sessions, analyze them, and discover similar issues
  • UX research: examine user navigation patterns and identify frustration points
  • Customer support: retrieve all sessions for a specific user to understand behavior
  • Performance analysis: detect slow-loading content and behavioral patterns

常见问题

1

What are the requirements to run this server?

You need an OpenReplay account with API access, a valid API key and project ID, network access to OpenReplay API endpoints, and Python 3.8+.

2

How do I configure it with Claude Desktop?

Add the server to your `claude_desktop_config.json` under `mcpServers` with the `python` command pointing to `run_server.py` and environment variables for `OPENREPLAY_API_KEY` and `OPENREPLAY_PROJECT_ID`.

3

What analysis tools are available?

Tools include `search_sessions`, `get_session_details`, `get_user_session_history`, `analyze_user_journey`, `detect_problem_patterns`, `generate_session_summary`, and `find_similar_sessions`.

4

Can I run the server in Docker?

Yes. Use `docker-compose up` with environment variables in `.env`, or run `docker build` and `docker run` with the appropriate environment variables.

5

What analysis capabilities does it offer?

It detects rage clicks, form abandonment, dead clicks, and errors; maps page flows and action breakdowns; and provides AI-generated summaries and behavioral patterns.

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