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@agenvoy/Agenvoy

Self-hosted agent harness with MCP tools

Agenvoy runs on your machine and turns agent requests into completed work. It can break tasks into steps, call tools, keep memory, schedule recurring work, and repair or create tools when needed. It also acts as an MCP server and client so Claude Code, Codex, and other agents can share the same sandboxed tools.

508 stars45 forksGoUpdated 6d ago
Agenvoy (Demo) - What's the weather in Taipei?
邱敬幃 Pardn Chiu57 views • 3 months ago

Videos about this repo

Who it's for

Builders who want their agents to complete research, file work, and recurring tasks inside a machine they control.

What it delivers

You can make agents do multi-step work, reuse the same tools across assistants, and keep the whole workflow local and visible.

What it does

Auto tool generation

Builds and saves a new tool when no suitable one exists.

Self-scheduling

Creates recurring jobs from a single sentence and runs them in your environment.

Long-term memory

Keeps key context and notes for later sessions.

File search

Answers questions from local files and documents.

Sub-agents

Breaks work into steps and coordinates multi-agent tasks.

MCP server and client

Shares sandboxed tools with MCP-compatible agents and connects to external MCP services.

Live command output

Streams command progress to the TUI and web dashboard.

Secure file boundary

Asks for confirmation before sensitive file access or out-of-home actions.

How to get it

  1. 1Run this in a terminal
    curl -fsSL https://agenvoy.com/scripts/install.sh | bash
  2. 2macOS tip: If you run schedules on a MacBook, also run
    sudo pmset -c sleep 0
  3. 3First open PowerShell as an administrator, then list and install a Linux distribution
    wsl --online --list
    wsl --install <distribution-name>
  4. 4After installation, restart your computer, open a WSL terminal, and run
    curl -fsSL https://agenvoy.com/scripts/install.sh | bash

README

Agenvoy

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.

agenvoy%2FAgenvoy | Trendshift

Version License

English · 繁體中文

Taiwan-developed AI Agent Harness

Agenvoy is a Taiwan-developed AI Agent Harness 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.

Why Agenvoy

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.

  • Turns conversation into deliverable work — Research live data, organize files, and complete multi-step tasks with an agent that acts and reports the result.
  • Fills capability gaps itself — Creates, tests, and keeps a new tool when no suitable one exists, ready to reuse next time.
  • Shares one tool library across agents — Agenvoy, Claude Code, Codex, and other agents use the same sandboxed tools instead of rebuilding them.
  • Keeps automation running — Create schedules in one sentence; recurring work runs in your environment and pushes the result.
  • Makes every step visible and controllable — Command output streams to the TUI and Web dashboard, while sensitive paths and restricted actions still require confirmation.
  • Connects models and external services freely — Route models by task and configure image generation, STT, TTS, stdio/HTTP MCP servers, and OAuth.
  • Provides private access from anywhere — The local daemon connects outward to Telegram and Discord, without making your host public or opening inbound ports.

What you can do with it

Ask live questions and get live answers (Web Search / Tool Generate)

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.

Web Search / Tool Generate demo

Turn one sentence into automation (Scheduler)

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.

Scheduler demo

Ask questions about your local files (File Search / RAG)

Find all invoices from last year

Which document mentions Prompt guide?

The agent searches your local files and answers directly.

File Search / RAG demo

Finish multi-step work (Skills / Sub-agents)

Summarize today's GitHub commits and generate a progress report

The agent breaks down the task, calls tools, combines results, and replies.

Skills / Sub-agents demo

Work with the agents you already use (MCP Server)

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

Claude Code creates a weather tool (1)

Codex reuses it and creates a crypto tool (2)

Agenvoy tests both tools (3)

Who it's for

If you want AI to complete work—not merely respond—within an environment you control, Agenvoy is for you:

  • People who want to turn research, file work, and recurring reporting into reusable automation
  • Developers who want a self-hosted agent with local data control and sandbox guardrails
  • Teams that want Claude Code, Codex, and other agents to share tools instead of rebuilding them
  • Technical operators who need private access to a local agent through the Web, Telegram, or Discord

Drive Your Agent From the Browser

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 Web Dashboard demo


Chatbot Integrations

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.


One-line install

macOS / Linux distributions

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 0

This prevents sleep from interrupting schedules.

Windows (via WSL)

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

Developer Recommendations

A cost-effective model setup to get started:

  1. Choose a subscription model for everyday primary use, such as:
    • GitHub Copilot ($10/mo) — pick gpt-5.6-luna: its quota drains slowly enough for daily use and it is capable enough for most work
    • OpenAI ChatGPT Plus ($20/mo)
    • SuperGrok ($30/mo)
  2. For a free trial, you can apply for a free NVIDIA NIM API token and try nvidia/nemotron-3.5-lightning-30b-a3b. It is not a large model, but it is a good choice for trying out Agenvoy at no cost.

Core capabilities

CapabilityDescription
Auto tool generationBuilds and saves tools when they're missing
Self-schedulingCreate cron jobs with a single sentence
Long-term memoryRetains key info and context
Knowledge notesReads the notes you keep, before it answers
File searchAnswers from your local files
Sub-AgentMulti-agent collaboration
MCP clientConnect to external MCP services via official go-sdk (live tool refresh)
MCP serverExpose sandboxed tools to any MCP-compatible agent
Reasoning guidesOn-demand rules via reasoning_guide(topic=...)
Tool MarketShare and install tools
Image generationGenerate images through a configured provider
Live command outputStream run_command progress to the TUI and Web dashboard
Secure file boundaryConfirm sensitive paths and out-of-home access before granting them
MCP OAuthLog in to HTTP MCP servers and persist tokens in the OS keychain
TranscriptionAudio and video to text
Self-improvementAuto-fixes after execution failures

Docs

Full documentation at agenvoy.com/docs

License

This project is dual-licensed.

  • Open sourceGNU Affero General Public License v3.0. You may use, modify and distribute it, provided derivative works and any network-accessible service built on it are released under the same license, source included.
  • Commercial — for use that cannot meet the AGPL-3.0 source-disclosure requirement, a commercial license is available. See COMMERCIAL.md.

Author

Just open an issue to share an idea.

Agenvoy contributors

©️ 2026 邱敬幃 Pardn Chiu

Files in the repo

Repository payload16 top-level entries
  • .github
  • cmd
  • configs
  • doc
  • extensions
  • internal
  • page
  • .gitattribute
  • .gitignore
  • COMMERCIAL.md
  • go.mod
  • go.sum
  • LICENSE
  • makefile
  • package-lock.json
  • README.md

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