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⇱ A system for managing project to-do lists with change logging | Glama


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A system for managing project to-do lists with change logging

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  • Why this server?

    This server is the best fit as its description perfectly matches the request: it is designed for 'logging changes, tracking project phases, and keeping architecture docs synchronized' while maintaining 'consistent project documentation and progress logs' in a human-readable format.

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    Enables maintaining consistent project documentation and progress logs across development workflows. Provides tools for logging changes, tracking project phases, and keeping architecture docs synchronized with day-to-day development work.
    Last updated
    1
  • Why this server?

    This server specifically enables task management (creating the initial checklist) using plain Markdown files, supporting the core request to manage state and checklists within a human-readable document format.

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    Enables AI-native task management using plain markdown files to create, update, query, and organize Epics, Stories, Tasks, and Milestones without requiring a database.
    Last updated
  • Why this server?

    This tool focuses on logging activities and changes ('log what changes were made each query') directly into 'daily markdown worklog files,' fitting the core documentation and logging requirements.

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    A Model Context Protocol server that enables AI tools to automatically log their activities with detailed metrics like timestamps, token usage, and costs into daily markdown worklog files.
    Last updated
    1
    3
    MIT
  • Why this server?

    Since the workflow requires maintaining a Markdown document of state, a secure filesystem manipulation tool is essential for reading, writing, and modifying those files reliably.

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    Enables secure filesystem operations with directory sandboxing and optional read-only mode. Supports file reading/writing, directory management, file searching, and text operations while restricting access to specified directories.
    Last updated
    12
  • Why this server?

    This server is optimized for managing Markdown documents through CRUD operations, directly supporting the maintenance and updating of the 'human readable (Markdown) document of the project's state.'

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    An MCP (Model Context Protocol) server for efficiently managing Markdown documents in Cursor AI IDE, supporting CRUD operations, search, and metadata management.
    Last updated
  • Why this server?

    This specifically converts AI agent plans into structured markdown task lists, helping the agent manage the initial 'to-do list' and track movement down the 'checklist' within the documentation structure.

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    An MCP server that converts Cursor agent plans into structured markdown task lists and organizes them in your repository, helping you track AI-generated plans and recommendations as actionable specifications.
    Last updated
    12
    MIT
  • Why this server?

    Useful for the logging requirement, as it 'Logs and analyzes Claude conversations in structured markdown format,' effectively recording the queries and responses that result in changes.

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    Enables intelligent conversation management with 4 AI agents that provide semantic analysis, pattern discovery, automatic documentation, and relationship mapping. Logs and analyzes Claude conversations with 70% token optimization and multi-language support.
    Last updated
    2
  • Why this server?

    While internal Markdown files handle logging, Todoist is an excellent external tool for generating and managing the initial 'to-do list' checklist and tracking its status ('moving down the checklist').

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    A comprehensive MCP server that provides full integration between Claude and Todoist, enabling task, project, section, and label management through 24 different tools with the complete Todoist API.
    Last updated
    30
    36
    6
    MIT
  • Why this server?

    This server is excellent for logging changes, as it 'automatically generates structured release notes from Git repository tags, analyzing differences between tags and saving formatted Markdown output.'

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    A Model Context Protocol server that automatically generates structured release notes from Git repository tags, analyzing differences between tags and saving formatted Markdown output to the .iris directory.
    Last updated
    1
    3
    MIT