Chat Logger
N/A
About
Capture and preserve chat dialogues in Markdown format, including timestamps and role details, ideal for archiving and evaluating discussions.
Capture and preserve chat dialogues in Markdown format, including timestamps and role details, ideal for archiving and evaluating discussions.
Discover web content and YouTube video transcriptions effortlessly with the Model Context Protocol (MCP). Easily convert HTML to Markdown format and pinpoint timestamps for convenient reference during discussions.
Efficient debugging solution that captures and showcases MCP log data from Claude software on macOS, Windows, and Linux systems, facilitating the resolution of integration challenges.
Gain valuable insights from your local Cursor chat history with a comprehensive Model Context Protocol (MCP). Uncover key development trends, usage patterns, and coding tips through advanced conversation search capabilities, detailed analytics generation, and versatile data export options. Elevate your development experience with tailored assistance based on extracted MCP data.
Experience seamless data retention through a cutting-edge Model Context Protocol (MCP) offering efficient text storage and retrieval features, enriched with advanced tagging options. This protocol ensures effortless information organization, searchability, and administration within dialogues, leveraging a secure local JSON repository.
Enhances your organization by incorporating a system for managing personal knowledge, storing, and organizing conversation notes directly on your device.
Easily syncs with markdown documents and Apple Notes to automatically organize and style conversational data from Claude for convenient retrieval and distribution.
Enhance your project workflow with a structured memory system offered by the Model Context Protocol (MCP). By leveraging markdown file storage, this protocol ensures seamless retention of context during chat sessions. Boosting efficiency further is the integration of Lunr.js indexing, facilitating easy access, updates, and associations with stored memories.
Empower AI virtual assistants by granting them entry to documents via a customizable server that transforms HTML into Markdown. This setup allows for monitoring tool interactions and examining the provided context.