Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
A coding and development harness on local models or hosted APIs, for code, review, research and ops.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
CODEZAIKU_DRIVENecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"codezaiku": {
"command": "npx",
"args": [
"-y",
"@wyrdsekai/codezaiku-mcp"
],
"env": {
"CODEZAIKU_DRIVE": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add codezaiku --env CODEZAIKU_DRIVE=your-value -- npx -y @wyrdsekai/codezaiku-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"codezaiku": {
"command": "npx",
"args": [
"-y",
"@wyrdsekai/codezaiku-mcp"
],
"env": {
"CODEZAIKU_DRIVE": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"codezaiku": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@wyrdsekai/codezaiku-mcp"
],
"env": {
"CODEZAIKU_DRIVE": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
CODEZAIKU_DRIVE envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub Wyrdsekai, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.3.19) llegó al registro hoy.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Up-to-date docs for AI agents
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
Solo se muestra el principio; lee el resto en el repo