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ADHD Progress Hub

Updated October 10, 2026

Overview / Description

ADHD Progress Hub is an open-source AI developer tool that preserves coding-session continuity so AI assistants like Claude Code, Cursor, and Codex can resume context instead of starting cold. It keeps a record of unfinished work as named threads, each holding progress notes and concrete next steps, so a developer who switches tools or returns after a break can pick up exactly where they left off. Before a new task begins, its overlap detection checks existing threads for duplicate effort, which matters when the same project is touched from several AI coding environments. The hub exposes three interfaces from one store: the MCP protocol for AI assistants to read and write progress directly, a REST API, and a web dashboard for humans. Work is held in a SQLite database alongside Markdown progress files, and the project recommends Docker Compose for a persistent self-hosted server, with an optional local subprocess mode for single-machine setups. Optional integrations include GitHub or Gitea sync, OpenClaw notifications, and local transcript indexing, plus reminders on once, per-session, daily, or random schedules to resurface stale threads. Because it is MIT-licensed and self-hosted, teams keep all session memory on their own infrastructure. For developers evaluating the best AI tool for cross-session memory, ADHD Progress Hub is a self-hosted option that treats progress as shared state across every assistant that connects.

Used For

Keeping cross-session memory for AI coding assistants: tracking unfinished threads, next steps, and detecting duplicate work across Claude Code, Cursor, and Codex.

Pricing

Plan

Free

Free — MIT-licensed open source; self-host at no cost (you provide the server/Docker host)

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Pros & Cons

Pros

  • Threads store progress notes plus concrete next steps so an assistant resumes exactly where it stopped
  • Overlap detection flags duplicate work before a new task starts
  • Three interfaces over one store: MCP for AI assistants, a REST API, and a web dashboard
  • Self-hosted on SQLite plus Markdown files, so session memory stays on your own infrastructure
  • Optional GitHub/Gitea sync, OpenClaw notifications, and scheduled reminders for stale threads

Cons

  • Self-hosting via Docker Compose means setup and maintenance fall on the user
  • Value depends on assistants that speak MCP; non-MCP tools only get the REST API or dashboard
  • No hosted or managed option — everything runs on your own machine or server
  • Early-stage open-source project without a commercial support path

Questions & Answers

Alternatives

Model-context memory servers and task trackers such as other MCP memory servers or lightweight dev task tools like TODO/thread managers.

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