Rooの活動を自動的に記録するMCPベースのロギングシステム
Rooの活動を自動的に記録するMCPベースのロギングシステム. Exposed over MCP by the roo logger mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
Roo Activity Logger is an MCP (Model Context Protocol) server that automatically records AI coding assistant development activities — including command executions, code generation, file operations, and more. It supports Claude Code, Cline, Roo-Code, and other MCP-compatible AI assistants. All logs are saved in JSON format, making it easy to search, analyze, and restore context at any time.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
Everything the assistant can do here goes through one of these:
Notes — The Notes tool exposed by this serverParameters — The Parameters tool exposed by this serverThis sits in the monitoring and observability group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Roo Logger's toolset — Notes, Parameters — is a fair guide to whether it matches your workflow. It is maintained by annenpolka; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Notes | The Notes tool exposed by this server. |
| Parameters | The Parameters tool exposed by this server. |
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Automates browser interactions and enables Large Language Models (LLMs) to interact with web pages through Playwright and Chrome DevTools Protocol
Guides tool usage by providing recommendations for MCP tools at each problem-solving stage.