Kenaz Harness
The Kenaz Harness is the desktop AI application you install and run on your own machine. Open it, pick an AI provider, and start chatting — ask it to read files, run searches, connect to services via MCP, and more. Everything it does is written to a local audit log so you always have a record of what happened.
The Harness is open source: github.com/kameas-ai/kenaz-harness. It runs standalone, or inside the Kenaz Workbench if you prefer an all-in-one sandboxed environment.
:::tip Ready to get started? Jump straight to the Quickstart — you'll be chatting in about five minutes. :::
What you can do with it
- Chat with any AI provider you choose. Bring your own API key for Anthropic, OpenAI, OpenRouter, AWS Bedrock, Azure OpenAI, Google Gemini, Ollama, or any OpenAI-compatible endpoint. Your keys stay in your OS keychain — they never reach a Kameas server. See Providers.
- Give the model real tools. Built-in tools cover filesystem reads/writes, shell commands, and web search. Connect any MCP server to add GitHub, Slack, Postgres, Notion, and hundreds more. Every tool call is gated by a permission prompt before it runs — you decide what the model is allowed to do.
- Organize work into sessions and projects. Conversations are first-class objects: branch them, attach files, group them into projects, search across all of them. See Sessions.
- Build up shared context over time. Long conversations compact automatically; useful facts pin into long-term memory; team-wide guidance goes into signed context packs that land in every teammate's session.
- Keep a tamper-evident record of everything. Every prompt, response, tool call, and permission decision lands in a hash-chained local audit log before it's shown in the UI.
- Stay local-first — connect to Fleet only when you want to. By default the Harness is fully self-contained and nothing is sent to Kameas. Optionally sign in to Kenaz Fleet to receive pushed team configuration, a shared tool catalog, and settings sync across devices. See Connecting to Fleet.
How it's organized
The window has a left rail of primary views and a Settings hub for provider, security, and authoring configuration:
Left rail
| View | What it's for |
|---|---|
| Sessions | Chat with the model. New conversations, branches, projects. |
| Tools | Connected MCP servers and the built-in tool registry. |
| Workflows | Agentic multi-step recipes you can run or customize. |
| Contexts | Context packs — guidance injected into every matching session. |
| Memory | Inspect and edit what the model remembers across turns. |
| Artifacts | Files the model produced during a session. |
| Audit log | Browse and export the local audit log. |
| Settings | All configuration — providers, permissions, hooks, secrets, and more. |
Settings hub (reached via Settings in the left rail)
| Section | What's inside |
|---|---|
| Providers | Add / remove AI providers and pick the default model. |
| Bundles | Installed bundles — signed packs of providers, skills, and MCP recipes. |
| Secrets | Managed secret store for tool credentials and environment values. |
| Permissions | What's currently allowed and per-session permission grants. |
| Policy | Cedar-based policy rules pushed from Fleet or authored locally. |
| Hooks | Pre-send / post-send shell or built-in hooks that run on every turn. |
| Compaction | Tune how long conversations are summarized. |
| Slash Commands | Custom slash-command library. |
Where to next
New here? Follow the onboarding path:
- Quickstart — install, add a provider, send your first message (5 minutes).
- Using the Harness — sessions, tools, memory, and daily patterns.
- Features — per-feature reference for everything the Harness can do.
- Providers — detailed setup for each AI provider.
- Connecting to Fleet — optional team features.
Something not working? See Troubleshooting & FAQ.