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    MCP server for coding-os, a cognitive operating system that gives AI agents memory, structure, and discipline. It exposes tools for project management, task tracking, knowledge graphs, and cognition traces to Claude Code and Codex.
    89
    32 PyPI
    6
    Apache 2.0
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    An MCP server that audits a project for documentation, rules, skills, and knowledge artifacts, compares against a reference concept catalog, and generates a prescription plan with frontmatter todos to guide creation of missing or incomplete elements.
    8 npm
    MIT
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    Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.
    10 npm
    Apache 2.0
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    Enables pipeline-driven task management for AI coding agents, with stage-gated workflows, dependency tracking, artifact versioning, and multi-agent collaboration.
    773 npm
    22
    MIT
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    Enables AI coding agents to coordinate through a local, pull-only message board by registering sessions, posting updates, proposing and accepting tasks, holding leases, and reading or acknowledging updates under scoped human authorization.
    8
    MIT
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    MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.
    24
    6
    MIT
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    Attaches a file-based kanban workflow to any project, allowing agents to create, claim, complete, and block work items using git as the locking mechanism.
    MIT
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    Enables Codex projects to read Git-backed kickoff, acceptance, handoff, progress, and next-step context, and to append validated, audited progress events through scoped MCP tools. This supports visible agent progress, resumable sessions, and safer handoffs.
    MIT
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    Enables AI agents to maintain project continuity through a file-based state hub with tasks, phases, and handoff snapshots. Provides MCP tools for reading and updating project state, with gatekeeping enforced via real-state evaluation and per-tool authorization.
    3
    MIT
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    maintenance
    Enables any MCP-capable coding agent to share one plain-Markdown project state — goals, tasks, decision logs, and session handoffs — stored in a project's .apm/ directory, with lock-safe concurrent writes and consistency checks that flag stale, blocked, or unowned work. This lets multiple agents and a human CLI resume work across interrupted sessions without a database or external service.
    MIT
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    Enables people and their AI agents to share a kanban board whose tasks, hand-offs, reviews, notes and alerts live as markdown files in a private GitHub repo, with per-person access control. Works from Claude, ChatGPT, Claude Code, Codex or any MCP-speaking client, and can draw the board inside chats.
    399 npm
    AGPL 3.0
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    maintenance
    An MCP server enabling AI coding agents to interact with a task tracker that enforces rules server-side, replacing markdown files and hooks with a database, CLI, and web UI.
    23 npm
    2
    MIT
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    A task orchestration system for AI agent teams that provides a Kanban dashboard and 12 MCP tools to manage multi-step workflows with DAG dependencies. It enables agents to coordinate through task threads, automated retries, and real-time webhook notifications.
    31
    MIT
  • A
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    Enables agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited progress events with matching Git commits through short-lived scoped credentials.
    MIT
  • A
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    quality
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    maintenance
    Enables AI agents to retrieve Git-backed project context, handoff packages, progress, and next steps, and to append validated progress events with matching project-record commits. This supports visible agent progress, resumable work, and safe handoffs while keeping high-risk actions outside the MCP surface.
    MIT