Taiwan-built, self-hosted AI agent harness in a single Go binary — writes its own tools, sandbox-tests them, and shares them over MCP with Claude Code and Codex.
Developer toolsGo · JavaScriptGitHub @pardnchiuOnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
Self-hosted AI agent harness in a single Go binary — writes, sandbox-tests and repairs its own tools, and lets Claude Code, Codex and any MCP client build and share them.
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
Make AI do the work on your computer—not just talk about it
Open source, single Go binary that runs on your computer. From live research and file work to automation,
Agenvoy takes action and delivers results; through MCP, it shares sandboxed tools with Claude Code, Codex, and other agents.Read the full README ↗Agenvoy is a Taiwan-developed AI Agent Harness by Pardn Chiu, built to turn conversation into completed work on your computer. It coordinates models, context, tools, real-time data, task routing, memory, schedules, and execution in one workflow, while keeping control of your files and environment in your hands. Through the Web interface, it also supports hands-free voice interaction with natural speech, wake-word detection, and interruptible spoken replies; the full result remains available in the chat.
A chat can give you an answer; work needs a result. Agenvoy breaks requests into steps, calls tools, and delivers outcomes on your computer—while you retain control of files, tools, schedules, and working context.
Agenvoy has already implemented the design directions below, and other teams have since adopted similar approaches, confirming that these directions solve real problems agents face in practice. Every milestone links to a public commit or release, so you can check it yourself.
| Shipped in Agenvoy | Design | Same direction elsewhere |
|---|---|---|
| 2025-06-28 Implement core application2025-06-29 add traditional memory structure | Summary-based memory for unbounded context | 2025-11-24 Claude client-side compaction |
| 2026-01-04 bubblewrap sandbox2026-02-01 harden bubblewrap sandbox2026-03-07 block sensitive paths and credentials2026-03-18 sandbox execution with bubblewrap | Sandbox mode for secure agents | 2026-03-16 NVIDIA NemoClaw |
| 2026-02-07 Copilot device code login2026-04-04 OpenAI Codex (OAuth) provider | Sign in with an existing AI subscription | 2026-09-29 Pi 0.99.0 Sign in with ChatGPT |
| 2026-02-27 LLM-driven agent routing2026-03-10 2026-04-15 2026-06-10 2026-09-11 2026-09-11 |
What's the weather in Taipei?
The agent finds current data, calls tools, and gives you the answer.
If a tool doesn't exist, it builds one.
Report TSMC stock price every morning at 8am
The agent asks:
- Where to push results
- What format you want
- When to run
Then creates the schedule automatically.
Find all invoices from last year
Which document mentions Prompt guide?
The agent searches your local files and answers directly.
Summarize today's GitHub commits and generate a progress report
The agent breaks down the task, calls tools, combines results, and replies.
Agenvoy is also an MCP server.
Claude Code, Codex, OpenCode, and other AI agents can connect and:
- Use all your sandboxed tools
- Auto-build new tools when none exist
- Share every tool across all agents
One line of config. Instant shared tool library. Tools created in the demo:
fetch_weather·fetch_crypto_price
If you want AI to complete work—not merely respond—within an environment you control, Agenvoy is for you:
Manage sessions, tools, schedules, and memory from a browser. The dashboard ships inside the binary — start the daemon and open http://127.0.0.1:17989. It is served by your own machine, so nothing leaves your device.
Agenvoy currently supports Telegram and Discord as chatbot channels. The local daemon initiates outbound connections to these platforms, so you only need to configure a bot token—without exposing inbound ports, setting up a reverse proxy, or making your host public.
Since v0.34.4, Telegram and Discord have paused the default flow that automatically replies to voice input with voice output. You can still use STT/TTS tools to generate audio and send the resulting audio files to either channel.
Run this in a terminal:
curl -fsSL https://agenvoy.com/scripts/install.sh | bash
macOS tip: If you run schedules on a MacBook, also run:
sudo pmset -c sleep 0This prevents sleep from interrupting schedules.
First open PowerShell as an administrator, then list and install a Linux distribution:
wsl --online --list
wsl --install <distribution-name>
After installation, restart your computer, open a WSL terminal, and run:
curl -fsSL https://agenvoy.com/scripts/install.sh | bash
A cost-effective model setup to get started:
gpt-5.6-luna: its quota drains slowly enough for daily use and it is capable enough for most work/model add and add gemma4:31b. The free plan has a usage cap; Shift+U shows how much of it is left.| Capability | Description |
|---|---|
| Auto tool generation | Builds and saves tools when they're missing |
| Self-scheduling | Create cron jobs with a single sentence |
| Long-term memory | Retains key info and context |
| File search | Answers from your local files |
| Sub-Agent | Multi-agent collaboration |
| MCP client | Connect to external MCP services via official go-sdk (live tool refresh) |
| MCP server | Expose sandboxed tools to any MCP-compatible agent |
| Reasoning guides | On-demand rules via reasoning_guide(topics=[...]) |
| Tool Market | Share and install tools |
| Image generation | Generate images through a configured provider |
| Live command output | Stream run_command progress to the TUI and Web dashboard |
| Rich chat rendering | Web chat renders charts, Mermaid diagrams, math, and highlighted code |
| Secure file boundary | Confirm sensitive paths and out-of-home access before granting them |
| MCP OAuth | Log in to HTTP MCP servers and persist tokens in the OS keychain |
| Transcription | Audio and video to text |
| Self-improvement | Auto-fixes after execution failures |
Full documentation at agenvoy.com/docs
This project is dual-licensed.
Under section 7(b) of the AGPL-3.0, the License and Source entries in the Other group of the web interface's Config > System tab must be preserved: they carry the copyright notice, the warranty disclaimer, the license statement, and the corresponding-source link that section 13 requires. They may be relocated or restyled while remaining prominently visible, but not removed or hidden. A commercial license removes this requirement.
Just open an issue to share an idea.
©️ 2026 邱敬幃 Pardn Chiu
| Route each task to the model best suited to it |
| 2026-09-14 Copilot auto model selection tiers: efficiency / balance / intelligence2026-09-29 Pi 0.99.0 virtual models: per-request model and thinking level2026-09-29 Pi 0.99.0 classifier models |
| 2026-03-23 script tool support with sandboxed execution2026-05-14 script tool scaffolding skill2026-06-05 script tool runtime metadata | Custom JS / Python tools run in the sandbox | 2026-09-29 Pi 0.99.0 codemode: model-written JavaScript in a QuickJS sandbox |
| 2026-04-02 deferred tool loading with search_tools2026-05-05 MCP client adapter with stdio/HTTP transports2026-06-07 tool search registry2026-08-08 MCP OAuth flow | Load tools on demand instead of declaring them all | 2026-09-29 Pi 0.99.0 built-in MCP + tool_search |
| 2026-04-17 invoke_subagent tool2026-04-25 session action logs2026-04-25 session log streaming endpoint2026-04-28 subagent name dispatch | Invoke sub-agents and track their logs | 2026-08-03 Claude Code cross-session messaging |
| 2026-05-28 extension tool loading2026-05-28 extension install and upload skills2026-05-29 extension marketplace2026-06-08 ext_ extension tools and scaffolding | Everything is a plugin | 2026-08-13 DeepSeek Harness: everything is a plugin |
| 2026-06-03 ask_user interruption async resume2026-06-04 preserve in-progress action memory across interruptions2026-06-29 pending task resume2026-07-03 write_todo checklist flow | Resume long tasks from a checkpoint | 2026-08-04 pi harness v2 in-memory storage 2026-08-05 pi indexed harness recovery queries2026-08-05 pi validate harness recovery record logs2026-08-05 pi harness v2 jsonl backend2026-08-06 pi atomic writes + torn-tail truncation2026-08-14 pi AgentHarness R3 generation recovery2026-08-14 pi AgentHarness R4 tool execution |