Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
A coding and development harness on local models or hosted APIs, for code, review, research and ops.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
CODEZAIKU_DRIVEYou need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"codezaiku": {
"command": "npx",
"args": [
"-y",
"@wyrdsekai/codezaiku-mcp"
],
"env": {
"CODEZAIKU_DRIVE": "your-value"
}
}
}
}Run this in your terminal
claude mcp add codezaiku --env CODEZAIKU_DRIVE=your-value -- npx -y @wyrdsekai/codezaiku-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"codezaiku": {
"command": "npx",
"args": [
"-y",
"@wyrdsekai/codezaiku-mcp"
],
"env": {
"CODEZAIKU_DRIVE": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"codezaiku": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@wyrdsekai/codezaiku-mcp"
],
"env": {
"CODEZAIKU_DRIVE": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
CODEZAIKU_DRIVE envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account Wyrdsekai, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.3.19) reached the registry today.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
A coding and development harness that runs on local models or hosted APIs. It is an AI coding agent for your terminal, like Claude Code or aider, that works with a small model on Ollama, llama.cpp, LM Studio or any OpenAI-compatible server. It also reviews git diffs, repairs a broken docker compose stack with rollback when you allow it, reports security problems in a server's Docker containers, researches questions with cited sources, and runs as an MCP server, an ACP agent or a command that prints JSON for other agents.
Most agents like this assume a frontier model behind someone else's API. CodeZaiku is built the other way round — a 9B on hardware you own — and the harness does the work that makes that viable: deterministic evidence instead of model guesses, a guard stack around anything that acts, and verification with rollback on every change.
It runs against any OpenAI-compatible server and ships no weights. The reference tier is a 9B.
→ [ARCHITECTURE.md](docs/ARCHITECTURE.md) — how it works → [LIMITATIONS.md](docs/LIMITATIONS.md) — the measured numbers
You need an OpenAI-compatible model server, and a JDK 21+ unless you take a build that carries its own Java runtime (from 0.3.2, one per platform; the installer picks one when Java is missing). CodeZaiku ships no weights.
Linux is the supported platform. macOS runs the coding and research surfaces (and can operate remote Linux hosts over ssh); Windows works under WSL2. There is a container image. See [PLATFORMS.md](docs/PLATFORMS.md).
At a terminal, for yourself — carry on below; the commands are in *What you can do with it*.
Underneath another agent or orchestrator — CodeZaiku is a backend as well as a tool. It speaks a CLI-subprocess contract (codezaiku run), ACP (codezaiku acp) and MCP (codezaiku mcp). The contract, the result shape and the failure modes are in [DEPLOYING_AS_A_BACKEND.md](docs/DEPLOYING_AS_A_BACKEND.md); start there rather than here.
Underneath Wyrdsekai — CodeZaiku is released under the Wyrdsekai umbrella and is one of the coding backends Wyrdsekai can summon: you ask the companion for something, it hands the work to CodeZaiku. [WITH_WYRDSEKAI.md](docs/WITH_WYRDSEKAI.md) is the short version of the page above — just the wiring, and the two things that trip people up. Nothing here depends on it; CodeZaiku runs standalone.
| path | needs | good for | ||
|---|---|---|---|---|
| one-line install — `curl … \ | sh, or irm … \ | iex` on Windows | a JDK 21+, or nothing: without one it takes the build with its own runtime | the recommended path. Verifies the download against the release checksums |
| release tarball — unpack and run; nothing to build | a JDK 21+ | doing it by hand, or air-gapped | ||
Docker — packaging/docker/Dockerfile | docker only | trying it with nothing on the host | ||
`.deb` — from the release, or packaging/deb/build-deb.sh | a JRE, pulled automatically by apt | Debian/Ubuntu, no build | ||
from source — scripts/install.sh | a JDK 21+ and network for the build | development |
There is one binary artifact and it is platform-independent. CodeZaiku is JVM bytecode with no native parts, so the same tarball installs on Linux, macOS and Windows — there is no .pkg or .msi to look for, and none is needed.
Linux is the reference platform. macOS and native Windows are measured too, and the installer is verified on all three from a clean unpack. On Windows, install from Git Bash — the harness shells out through bash, and Git for Windows supplies it. See [PLATFORMS.md](docs/PLATFORMS.md) for per-platform steps and for what does and does not work on each.
Linux and macOS:
curl -fsSL https://codezaiku.org/install | sh
Windows, from PowerShell (you also want Git for Windows — the harness shells out through its bash):
irm https://codezaiku.org/install.ps1 | iex
Only the script comes from codezaiku.org; the artifact and the checksums both come from the same GitHub release. What that URL serves is scripts/install-remote.sh (and scripts/install.ps1) from this repository, verbatim — read them here first if you would rather, and diff them against what the site serves. Both installers fetch the release tarball and verify it against the release's own `SHA256SUMS` before installing anything — a mismatch refuses rather than proceeds. Only the script comes from the URL above; the artifact and the checksums both come from the same GitHub release, so the script cannot hand you a payload those checksums do not match. Piping a script into a shell is worth being wary of in general: fetch it, read it, then run it if you would rather.
They install to ~/.local (or %LOCALAPPDATA%\Programs on Windows). CODEZAIKU_PREFIX puts it somewhere else, CODEZAIKU_VERSION pins a release.
No JRE on the machine yet? On Debian or Ubuntu, take the .deb from the latest release instead — it declares a JRE dependency, so apt installs one for you:
sudo apt install ./codezaiku_0.1.1_all.deb
The one-liners deliberately do not install a JRE themselves: a script piped into a shell should not be reaching for sudo. They check for one; when it is missing they install the build for the platform that carries its own runtime (codezaiku- - .tar.gz, from 0.3.2; CODEZAIKU_RUNTIME=1 asks for it outright), and codezaiku update keeps such an install on its own kind.
To upgrade, run `codezaiku update now`, or the same install command again. update now takes the latest release, checks it against the release's SHA256SUMS and swaps it in; the next start runs it. When ResearchZosho is installed, it then asks ResearchZosho's own updater to do the same, and says what came of each. Each program's own updater replaces its files, so two programs updating at once never collide: the second finds the first at work and leaves it alone. On Windows, CodeZaiku cannot replace its own files while it runs, so there you run the install command again. The installers resolve the latest release each time and replace the old install rather than writing over it, so nothing stale is left behind. Your config and data in ~/.codezaiku are untouched. The .deb upgrades in place with sudo apt install ./codezaiku_ _all.deb and keeps /var/lib/codezaiku; if you enabled codezaiku.service, the upgrade does not restart it, it tells you to when it suits you.
Other ways: tarball by hand, .deb, from source
tar xzf codezaiku-0.1.1.tar.gz # unpacks a ready-to-run ./codezaiku
./codezaiku/bin/codezaiku --version # works immediately sudo mv codezaiku /opt/codezaiku sudo ln -s /opt/codezaiku/bin/codezaiku /usr/local/bin/codezaiku
On Debian or Ubuntu, sudo apt install ./codezaiku_0.1.1_all.deb — it installs to /opt/codezaiku, links /usr/bin/codezaiku, and lets apt pull a JRE. The systemd unit it ships is disabled; nothing starts on its own.
From source, if you want to build it yourself or work on it:
git clone https://github.com/Wyrdsekai/codezaiku.git && cd codezaiku
codezaiku on your PATH (~/.local by default;scripts/install.sh
codezaiku setup # the first ten minutes: the model (found, served on demand, or a hosted key), web search, your editor's agent over MCP, the library if wanted codezaiku model serve install # this machine's memory, on demand: the measured model, llama.cpp behind a proxy that starts it when asked and stops it after 20 idle minutes (on Linux llama.cpp's container for the GPU it finds: NVIDIA, AMD or Intel; Metal on macOS, Vulkan on Windows) codezaiku model detect # finds Ollama / llama.cpp / LM Studio / vLLM if running codezaiku model use http://localhost:8200 codezaiku model add deepseek openrouter deepseek/deepseek-v4.1-flash --prices 0.032/0.144/0.002 # a hosted model under a name, codezaiku model key openrouter --file ~/openrouter-key.txt # its key kept for its host,
codezaiku spend says what the jobs costcodezaiku doctor
codezaiku smoke
The install carries its own launcher, jars and knowledge library, and downloads nothing at runtime. It does not bundle a JVM — install.sh checks for a JDK 21+ and stops if it does not find one. No model weights are bundled either. scripts/install.sh --uninstall removes the program and keeps ~/.codezaiku — your config, learned cards, research findings and audit trail. --purge removes those too, after listing what will be lost and asking you to confirm.
To work in the repo without installing, bin/codezaiku runs from the checkout.
If you have no server yet:
docker run -d --name codezaiku-drive -p 8200:8200 \
-v /path/to/models:/models ghcr.io/ggml-org/llama.cpp:server-cuda \ -m /models/ .gguf --port 8200 --host 0.0.0.0 --jinja --ctx-size 32768
To use the models in your own AWS account (Amazon Bedrock) with your own AWS sign-in, see [BEDROCK.md](docs/BEDROCK.md).
--jinja is required — without it the model returns tool calls as prose and nothing works. See [MODELS.md](docs/MODELS.md) for what the harness needs from a model, what we measured on, and why codezaiku smoke is the check that matters.
sudo apt install ./codezaiku_0.1.1_all.deb # build it: packaging/deb/build-deb.sh
Installs to /opt/codezaiku with /usr/bin/codezaiku. A systemd unit is included but not enabled — CodeZaiku can modify live systems, so starting it is a deliberate act.
Every release asset ships with SHA256SUMS and a Sigstore bundle ( .sigstore.json):
sha256sum -c SHA256SUMS --ignore-missing
gh attestation verify codezaiku-0.1.1.tar.gz --repo Wyrdsekai/codezaiku \ --predicate-type https://codezaiku.org/attestation/release/v1
gh attestation needs GitHub CLI 2.49 or newer. An older gh reports unknown command with no hint why — check with gh --version before concluding the signature is bad.
The signature says the release workflow, running at that tag, blessed those exact bytes. It is an authenticity statement, not build provenance — the artifacts are built and validated on real hardware rather than in CI, because an artifact nobody ran is not one worth shipping. Release assets are immutable; a fix ships as a new version, never as a re-upload.
codezaiku help # all commands, grouped by intent
Talk to it
codezaiku chat ~/myproject
A coding assistant you talk to in your terminal — the same kind of tool as Claude Code, Codex CLI or aider, except the model behind it is yours to choose: one running on your own hardware, or a hosted API. You type what you want — "why does the login test fail?", "add a retry to the uploader", "find out how other projects handle this" — and it reads your code, makes changes, runs commands, or searches the web, then reports back. You steer it turn by turn.
By default it asks before changing or running anything, a
Only the beginning is shown; read the rest in the repo