Motif
Description
A unification layer for AI coding agent sessions — collect Claude Code, Codex and Cursor sessions across your team, search them, hand one session natively to another tool, and let your agents recall what the team already knows. Self-hosted.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
Motif
**A unification layer for AI coding agent sessions.** Open source, fully self-hosted.
Start in Claude Code, finish in Codex — the session comes with you, natively.
Your team writes code with Claude Code, Codex, and Cursor — each tool keeps its sessions in its own format, in its own corner. Motif collects them in one place, makes them searchable across tools and teammates, streams them live to a team dashboard, and can hand a session started in one tool over to another tool **natively** — the target tool treats it as its own history, not a summary.
Features (v1)
- Collect — a lightweight daemon watches Claude Code, Codex, and Cursor
sessions on each dev machine and syncs them live to your self-hosted server.
Sessions never leave your infrastructure. (Other open-source agent CLIs are on
the roadmap; open-weight models themselves — Hermes, Qwen, Llama via Ollama/OpenRouter — already work today
as the memory engine through the
openai-compatibleprovider.) - Native handoff — convert a Claude Code session into a real Codex rollout file.
codex resumepicks it up as its own session; continue exactly where you left off. - Recall — an MCP server that hands your agents the 1-2k tokens that matter instead of letting them re-derive the codebase every session. Deterministic (FTS + session graph + human notes), so it needs no API key.
- Ask a session — resume any past Claude Code or Codex session read-only on the machine that owns it and get an answer from the agent that lived it, not a summary.
- Session memory — the server distills sessions into entity-based notes (files, decisions, topics) with supersession and conflict detection, powered by a pluggable LLM provider (Anthropic, OpenAI, any OpenAI
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