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Shared memory layer for multi-agent coding workflows

Build a shared memory and coordination layer for people running multiple AI coding agents (Claude Code, Cursor, Codex, OpenCode) at once, so decisions, rules and task context persist across sessions and tools instead of being re-explained every time. A Windows/Linux equivalent, a team-focused paid tier, or a lighter single-purpose plugin (just the decision ledger, or just cross-agent memory) are all underserved angles since the example tool is free, individual-only and macOS-exclusive.

via Reddit
Original post

What to build

A lightweight, cross-platform (Windows/Linux) memory and coordination layer for solo devs running multiple AI coding agents (Claude Code, Cursor, Codex, OpenCode) that persists decisions, rules, and task context across sessions and tools via a local daemon plus editor/CLI plugins.

Devs juggling several AI coding agents lose shared context between sessions and have to re-explain decisions every time; a free macOS-only tool proved the concept but left Windows/Linux, teams, and lightweight single-purpose versions wide open.

Demand

Solo builders and small teams running Claude Code, Cursor, Codex, and OpenCode side by side want context to persist across tools and sessions instead of re-explaining rules and decisions each time; the existing tool's macOS-only, single-user limits leave this unmet for most developers.

  • r/SideProjectCommunity

    Reddit post: "I built a shared brain for my coding agents (with memory, coordination and decision graphs). I use Claude Code, Codex, Cursor"

  • Signal reportAnalysis

    Tool noted as free, individual-only, and macOS-exclusive, leaving Windows/Linux support, team-paid tiers, and lighter single-purpose plugins unaddressed

Stack

  • SQLite or DuckDB for local decision graph storage
  • LangGraph or custom state machine for coordination logic
  • Model Context Protocol (MCP) servers for agent integration
  • Tauri or Electron for cross-platform packaging
  • Rust or Go for a lightweight background daemon
  • GitHub Actions for CI across Windows/Linux builds

Solo + AI difficulty

The hard part is building reliable MCP-style hooks into each agent's session lifecycle across tools with different plugin models; cross-platform file-watching and daemon packaging also take real effort. A CLI-only decision-ledger MVP (no GUI, single-agent support first) is achievable in 2-4 weeks for one developer with AI assistance.

Entry threshold
Moderate: needs git worktree orchestration, an MCP-based control layer and a simple decision/memory store, which a solo builder can assemble in a few weeks with AI help, but it requires real systems and devtools fluency, not just a wrapper UI.
Window
6-12 months

Where to find first users

  • r/SideProject
  • r/ClaudeAI and r/cursor subreddits
  • Product Hunt launch
  • Indie Hackers community

Counter-signals & risks

  • Major AI coding tool vendors (Anthropic, Cursor, OpenAI) could natively build cross-session memory and coordination features, obsoleting third-party shared-memory layers

  • A free, single-developer tool with no stated roadmap or funding may not be sustained long enough to validate demand for a Windows/Linux or paid team version

  • Developers coordinating multiple agents may already rely on existing workarounds (shared markdown files, git-based context, existing memory plugins), reducing urgency for a new dedicated layer

Original title: I built a shared brain for my coding agents (with memory, coordination and decision graphs)

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Shared memory layer for multi-agent coding workflows — Nichr