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@codaph/codaph

v0.1.16

Published

Codex-first CLI/TUI for prompts, thoughts, diffs, and collaborative MuBit memory.

Readme

Codaph

Codaph is a terminal-first CLI interface for inspecting coding-agent activity with shared Mubit-backed memory.

Codaph is the result of a confusion - who prompted (this)? during our dev cycle. The prompt or code wasn't the problem but the lack of story around it. With agentic coding tools, we are shipping faster than ever but also missing out on so much story. Codaph aims to be the bridge and to also convince you to sign up to Mubit.

[!WARNING] Codaph is in beta and can break. Plus, its agentically engineered. Be mindful.

Once a legend said, if Pentagon can vibe code secret ops with AI, we can surely engineer a CLI with it.

Plans

  • [ ] Rust rewrite for the love of game and performance optimisation
  • [ ] Use Mubit state subscription for auto exec / scripting
  • [ ] Dependencies map and upgrade sync in Mubit
  • [ ] Plugin for coding agents
  • [x] MCP Server
  • [ ] Add support for
    • [x] Claude Code ✅
    • [ ] OpenCode
    • [x] Gemini ✅
    • [ ] Cursor
    • [x] Codex ✅

What's the Point of using a memory platform like Mubit

If you have more than 2 engineers working in parallel with various coding agents, it gets difficult to trace semantic reasoning and understand the story.

Onboarding a new engineer or a new agent becomes a problem with the coldstart. Using Mubit helps avoid it and build on top the semantic layer (of your own code).

The goal with Codaph is to enable a VCS that humans can use to understand the code story while we offload the tasks to agents.

Installation

Use one of the following methods.

npm / npx

npm i -g @codaph/codaph

From source (development)

git clone <your-repo-url>
cd codaph
bun install
bun run build

First-Time Setup (Keys)

Codaph uses Mubit for shared cloud memory and sync. Configure a Mubit API key before your first sync.

OpenAI is optional. If you add OPENAI_API_KEY, Codaph can produce OpenAI-assisted answers for codaph mubit query and TUI chat (m) using Mubit evidence. The default OpenAI model is gpt-4.1-mini, and you can override it with OPENAI_MODEL.

codaph setup --mubit-api-key <your-mubit-key>

# optional: OpenAI-assisted query/chat
codaph setup --openai-api-key <your-openai-key>

You can also set MUBIT_API_KEY, OPENAI_API_KEY, and OPENAI_MODEL as environment variables. If a Mubit key is missing, codaph init prompts for it.

Usage

Run Codaph from the project root you want to inspect.

# one-time key setup (recommended; can also use env vars)
codaph setup --mubit-api-key <your-mubit-key>

# one-time repo setup (wizard; detects .codex/.claude/.gemini and lets you multi-select)
codaph init

# daily sync (fast, Mubit-first)
codaph sync

# open terminal UI
codaph tui

# optional historical backfill from local agent history (Codex / Claude Code / Gemini CLI)
codaph import

# inspect sync and automation state
codaph status

codaph init also writes a reusable Claude Code MCP template at .codaph/mcp/claude-code.json. Use codaph mcp setup claude to print (or run with --run) the recommended claude mcp add ... command.

Optional query example (OpenAI-assisted if OPENAI_API_KEY is set, otherwise Mubit response):

codaph mubit query "what changed in auth?" --session <session-id>

If you are running from source, use bun run cli instead of codaph.

bun run cli init --cwd /absolute/project/path
bun run cli sync --cwd /absolute/project/path
bun run cli tui --cwd /absolute/project/path

MCP (Claude Code)

Codaph ships a local MCP server over stdio:

codaph mcp

Recommended setup (personal use):

codaph mcp setup claude --scope user --run

This uses Claude Code user scope (~/.claude.json) so one Codaph MCP config works across repos.

Project scope (.mcp.json) is also supported when you want a shared/team config. codaph init writes a copy/merge template at .codaph/mcp/claude-code.json.

See MCP Setup (Claude Code) for claude mcp add commands, JSON examples, and troubleshooting.

Documentation

Start with Quickstart for Mubit API key setup, optional OpenAI-assisted query/chat setup, and the recommended first-run flow.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests and documentation as appropriate.

License

Dual-licensed under either of the following, at your option:

  • MIT
  • Apache License 2.0

See LICENSE for the full text of both licenses.