FLUJO is a free, open source ai interaction & interfaces project written in TypeScript and released under MIT. It has 671 GitHub stars, 92 forks and 26 open issues, and was last pushed 33 hours ago. On this registry it ranks #142 of 156 tracked projects in AI Interaction & Interfaces, with 5 head-to-head comparisons available. It gained 43 stars over the last 30 tracked days.

What is FLUJO?

FLUJO is an open-source, local-first visual builder for multi-agent AI workflows that lets you connect models and apps, build agents as step-by-step recipes or expert visual flows, inspect every run, and expose those same agents through OpenAI-compatible and MCP endpoints, aimed at developers, automation builders, and technical teams that want their keys and data to stay under their own control.

What it is

FLUJO is a TypeScript application, licensed under MIT, that runs as a private workspace for building and operating AI agents. It is powered by the PocketFlow Framework and was built with Cline and Claude Code. The project lives in the agentic-AI and AI-interaction space: its topic list covers agentic-ai, agentic-framework, agentic-workflow, ai-chat, automation, autonomous-agents, llm-agents, mcp and mcp-client, and it is distributed as a local application with an installer, an npm package, and a hosted trial at try.flujo.com.co. The current version carried in the repository is 3.45.2, and the default posture is local-first: FLUJO stays on localhost unless it is deliberately opened to a private network or configured for public deployment.

The concrete problem it solves is the wiring work that sits between a model provider and a usable agent. Instead of hand-assembling provider connections, MCP servers, and scripted orchestration, and instead of handing API keys to a hosted agent platform, FLUJO provides visual builders for the flow, a guided setup, a run inspector, and endpoint exposure so the finished agent can be talked to, automated, or called from other software. Secrets are encrypted at rest in local storage, they never reach the browser, and the frontend only sees a masked placeholder even in DevTools, which means the working state of the agent and the credentials that drive it remain on infrastructure the operator controls.

Key capabilities

  • Two builder modes: simple step-by-step recipes for straightforward agents, and expert visual flows for more involved orchestration.
  • MCP-native operation as an MCP client, with MCP servers receiving their runtimes during installation.
  • Multi-model configuration covering OpenAI, Azure OpenAI, Anthropic (native or OpenAI-compatible), Google Gemini, X.ai (Grok), OpenRouter, and Codex.
  • Agents exposed through OpenAI-compatible and MCP endpoints so external software can call them.
  • Built-in debugger that lets every run be inspected step by step.
  • Secrets encrypted at rest with an optional custom encryption password, kept server-side and never sent to the browser.
  • Reusable global variables that bind a key once and reuse it across AI and connected-app configurations, plus encrypted workspace backup and restore from Settings.
  • Adjustable network access spanning localhost, private-network devices, and public deployment.

Who uses it and how

  • Individual developers running FLUJO on localhost who want a private AI workspace without sending keys to a third-party service.
  • Small teams that allow devices on a private network to reach a shared FLUJO instance while keeping the encrypted workspace under their own administration.
  • Automation builders who publish an agent through OpenAI-compatible or MCP endpoints and call it from other software rather than driving it by hand.
  • Operators who need a public deployment of the same agents and who configure network access accordingly.
  • Privacy-sensitive setups where secrets must stay server-side, including the masked placeholder behaviour that hides them from the frontend.

Getting started

The recommended path is the Windows installer flujo-setup.exe from the latest release, or the install script — irm https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.ps1 | iex on PowerShell and curl -fsSL https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.sh | bash on Linux and macOS. If Node.js is already present, npx flujo-ai runs a prebuilt FLUJO without installation, and try.flujo.com.co offers an online option.

How it compares

The material available for FLUJO names no comparable tools and no list of paid products it displaces, so on the evidence here it stands alone in this registry. The comparison axes the project does establish for itself are licence, hosting and cost model: it is MIT-licensed, local-first by default, and installable from source, npm, or an installer rather than sold as a subscription service.

When to use it — and when not to

Choose FLUJO when agent logic and credentials need to stay on hardware you administer, and when the same agent must be usable interactively, on a schedule, and from other software through OpenAI-compatible or MCP endpoints. A self-hoster should expect to operate a Node.js runtime, and to keep git, python and uv available on the PATH for MCP servers, since the npm route does not guarantee those runtimes; the encryption password for the workspace is also the operator's responsibility to hold. Anyone who wants a fully managed cloud agent platform with no local maintenance should look elsewhere, and the repository's 26 open issues suggest the project is still actively settling rather than finished.

project readme (upstream, from github) — read inline

FLUJO

Build private AI agents visually. Run them your way.

Connect your AIs and apps, build an agent, then talk to it, automate it, or call it from other software.

FLUJO is open-source and local-first. Start with the guided setup, build agents as simple step-by-step recipes or expert visual flows, inspect every run, and expose the same agents through OpenAI-compatible and MCP endpoints — while your keys and data stay under your control.

Simple + visual builders · MCP-native · Multi-model · Built-in debugger · Automation

Visit flujo.com.co → · Watch the 2:28 product film → · Install FLUJO ↓ · Explore features ↓ · Try FLUJO online →

MIT License Version

FLUJO is too complicated? You are missing a feature or are stuck on something? Hop into the Discord, or create an Issue on Github! We can only improve if we know what's wrong. It really helps a lot!

Watch FLUJO — Your AI. In Flow.

Click the preview to see FLUJO in motion.

image

⚡ Quick Install (recommended)

The installer sets up everything FLUJO needs (Git, Node.js, Python, uv, ripgrep), clones FLUJO, builds it, and creates a global flujo command. This is the recommended way to run FLUJO — MCP servers get all their runtimes too.

Windows installer (recommended) — click below to download the latest flujo-setup.exe:

Download Setup.exe — Windows Installer

Windows PowerShell — alternatively, press Start, type powershell, press Enter, copy & paste the command below and press Enter again:

irm https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.ps1 | iex

Linux / macOS — paste into a terminal:

curl -fsSL https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.sh | bash

Already have Node.js? You can also skip installation entirely and run a prebuilt FLUJO straight from npm — fastest start, but MCP servers may still need git / python / uv on your PATH (see Run via npx):

npx flujo-ai

Prefer to set it up manually? See Getting Started. To remove FLUJO later, see Uninstalling.

[!TIP] Stuck on MCP installation, the app, or anything else? Open a GitHub issue or join the Discord. I read every message and will do my best to get back to you within a day.

FLUJO Overview

The FLUJO home screen: connect once, then use your private AI workspace.

FLUJO is powered by the PocketFlow Framework and built with Cline, Claude Code, and a lot of love.

🌟 Key Features

🔐 Local-first Security & Workspace Controls

  • Local-first by default: keep FLUJO on localhost, allow devices on your private network, or configure it for a public deployment
  • Encrypted at rest: API keys and other secrets are encrypted in local storage, with an optional custom encryption password for extra protection
  • Never sent to the browser: secrets stay server-side — the frontend only ever sees a masked placeholder, even in your own DevTools
  • Reusable global variables: define a key once and bind it into any AI or connected-app configuration instead of pasting it repeatedly
  • Backup & restore your encrypted workspace from Settings

Settings — Network Access

🤖 AI Setup

  • Multiple providers: OpenAI, Azure OpenAI, Anthropic (native or OpenAI-compatible), Google Gemini, X.ai (Grok), OpenRouter, Codex, and local models via Ollama
  • Guided or expert setup: choose a gentle walkthrough, a faster guided path, or the complete configuration form
  • Claude Subscription: use your Claude Pro/Max plan directly (via the Claude Agent SDK) instead of a metered API key
  • Reusable connections: organize configured AIs into folders, mark favorites, and reuse them across agents and conversations

AI Setup — Configured AI Connections AI Setup — Guided Connection Wizard

🔌 Connected Apps (MCP)

  • Guided connection: let FLUJO research an app, choose from curated options, or enter a remote URL, GitHub repository, or local command yourself
  • Install from anywhere: search the official MCP Registry, use curated servers verified with FLUJO, or install manually from a GitHub repo / local folder
  • Full MCP capability support: tools, resources, prompts, roots (workspace folders), and sampling (let a server borrow one of your models under a trust policy you control)
  • Tool inspection & testing: browse and call a server's tools, resources, and prompts straight from its detail view
  • FLUJO as an MCP proxy: re-expose any server you've configured in FLUJO to other MCP clients (Claude Desktop, Cursor, Cline, …) over Streamable HTTP — configure a server once, use it everywhere

Connected Apps — Guided Setup

Configuring a server is a guided, three-step form (define it → install & build → define how to run it) with a one-click connection test before you save:

MCP Server Configuration

Every connected server gets a detail view to browse and test its tools, resources, and prompts directly:

MCP Tool Tester

🧩 Agent Builder

  • Simple mode: build an agent like a recipe, one plain-language step at a time, without touching a diagram
  • Expert visual mode: connect Start, AI, connected-app, subflow, and Finish nodes in a drag-and-drop graph
  • Branching & handoff: let a model hand off to another node/agent based on the conversation, build loops, or fan out into multiple specialists
  • Subflows: call another flow as a single step, with its own isolated state — reuse a flow like a function
  • Per-node tool & prompt scoping: decide exactly which tools, resources, and system-prompt fragments each node can see

Agent Builder — Simple Setup Agent Builder — Expert Visual Mode

Branching & handoff

Connect one node to several successors, then tell the model when to use each handoff tool from the "Agent Tools" tab of its Process Node:

Branching Branching handoff tools

Loops

Connect a node back to a previous one the same way to build a loop:

Loops

Orchestration & Subflows

Combine multiple handoffs and loops to build an orchestrator, or drop in a Subflow node to run another flow as a single, reusable step with its own isolated state:

Orchestration Subflow configuration

💬 Talk

  • One place to talk to every agent: select an agent and start a conversation from the Talk page
  • Live execution view: watch a run progress step-by-step in real time, with token usage and a context-window meter per conversation
  • Visual debugger: set breakpoints, step through a run node-by-node, and inspect state before/after each step
  • Human-in-the-loop tool approval: optionally require approval before any tool call executes, for any provider (including Claude Subscription's agentic tool use)
  • File & audio attachments, message editing, and conversation branching

Talk Interface

Step through a run node-by-node with the visual debugger, inspecting prep/exec state at every stop:

Visual Debugger

⏱️ Automations — Triggers

Run your flows automatically — on a schedule or when something happens — without opening the chat. FLUJO just needs to be running for triggers to fire.

  • Schedule: cron-style recurring runs (with second-level precision and catch-up for missed runs)
  • Webhook: trigger a flow via an authenticated HTTP call
  • File watch: fire when files change under a folder
  • MCP tool polling: periodically call a tool and fire on change, on new items, or let a model/checker-flow decide
  • URL watch: fire when a fetched page's content changes

Automation Triggers New Automation Trigger — Schedule, Webhook, File, Tool, Website, or Flow

Run history is kept per trigger, with the full output of every run one click away:

Automation Trigger Run Detail

As an example, a "watch a tool" trigger polling a WhatsApp MCP server can turn FLUJO into an autonomous auto-responder:

WhatsApp auto-reply demo

Meetings

  • Put multiple Agents into a shared conversation, so they can work on a task together
imageimage

🔄 External Tool Integration

  • OpenAI-compatible endpoint: point Cline, Roo Code, Cursor, or any OpenAI-SDK client at http://localhost:4200/v1, use any API key value, and pick a model named flow-
  • FLUJO as an MCP server (proxy): point an external MCP client at http://localhost:4200/mcp-proxy/ to reuse a server you configured once in FLUJO (localhost-only in the current version)

Note: FLUJO does not expose an Ollama-compatible server endpoint — use the OpenAI-compatible provider above to consume flows from other apps. (Connecting FLUJO to a local Ollama instance as a model provider is a separate, supported feature.)

📖 Built-in API Documentation

A searchable /docs page inside the app documents every REST endpoint FLUJO exposes (chat, conversations, models, flows, MCP, planned executions, env/encryption, backups) — useful when integrating FLUJO into your own tooling.

Built-in API Documentation

🚀 Getting Started

Manual installation:

Prerequisites

  • Node.js (v18 or higher)
  • claude code (optional, if you want to use Anthropic Subscription)
  • python (optional, if you want to use python-based MCP servers)
  • pip (optional, if you want to use python-based MCP servers that build with pip)
  • uv and/or yarn (optional, if you prefer these over npm or pip)
  • ripgrep (optional filesystem-search acceleration; the installer adds it automatically)

Installation

  1. Clone the repository:

    git clone https://github.com/mario-andreschak/FLUJO.git
    cd FLUJO
    
  2. Install dependencies:

    npm install
    # or
    yarn install
    
  3. Start the development server:

    npm run dev
    # or
    yarn dev
    
  4. Open your browser and navigate to:

    http://localhost:4200
    
  5. FLUJO feels and works best if you run it compiled:

    npm run build
    npm start
    

Run with Docker

On any machine with Docker, start FLUJO with one command:

docker compose up --build

Then open http://localhost:4200.

Use --build (not a bare docker compose up). The default compose file builds the image locally from this repo. A plain docker compose up only builds when no image exists yet — after you update the code it silently reuses the previously built image and runs the old version. --build rebuilds when the source changed and is a fast no-op when it hasn't.

  • Your data persists in flujo-workspaces (the workspace namespace and all non-default workspace data), plus the existing flujo-db and flujo-mcp-servers volumes mounted inside default-workspace. Reusing those two established volume names makes an upgrade retain existing flows, models, encrypted keys, chats, MCP configs, and installed server clones while every newly created workspace also survives docker compose down / up.
  • Updating: use git pull && docker compose up --build instead of the in-app updater. FLUJO detects it is running in a container and shows this in the update settings. (docker compose pull only helps if you switched the service to a published image: — the default builds locally.)
  • Private/corporate CA for HTTPS MCP servers: mount your CA file and set FLUJO_EXTRA_CA_CERTS to its path (see the commented environment: block in docker-compose.yml).
  • Claude Subscription in-container: generate a token on your host with claude setup-token and pass it as CLAUDE_CODE_OAUTH_TOKEN.
  • fileWatch triggers: bind-mount the host folder you want to watch into the container (see the commented volume example in docker-compose.yml).
  • MCP Apps: Compose also publishes the shared sandbox listener on port 4201, loopback-only. Each App is loaded through its own http://.localhost:4201 browser origin. Keep both port mappings when using interactive MCP Apps.

⚠️ Security: FLUJO has no authentication layer and its git API runs commands on the server, so the port is bound to localhost only by default. Do not expose it on 0.0.0.0 / publish it publicly unless it sits behind your own authenticating reverse proxy on a trusted network.

Network exposure

Use Settings → Network access to choose one deployment posture:

  • Localhost (default) — only this computer; both listeners bind loopback.
  • Local Network — listen on all interfaces and accept private LAN addresses and this machine's hostnames.
  • Public — accept any hostname. FLUJO has no built-in authentication, so use this only behind an authenticating HTTPS reverse proxy.

The one setting controls the UI, API, OpenAI/MCP endpoints, Host/Origin guard, and MCP Apps sandbox binding together. Restart FLUJO after changing it.

MCP Apps require no additional configuration on localhost or a plain-HTTP Local Network install. FLUJO discovers the browser-visible host automatically and uses port 4201 for the sandbox. Hosted HTTPS deployments can optionally configure FLUJO_MCP_APP_SANDBOX_PUBLIC_URL with {app} as one complete hostname label, for example https://{app}.sandbox.example.com/sandbox.html, and proxy those wildcard hostnames to FLUJO's plain HTTP port 4201. Without wildcard DNS/TLS, set the same variable to a single shared sandbox origin instead (for example https://sandbox.example.com); the App key then travels in the authenticated sandbox URL. Preserve the browser's Host and Referer headers through the proxy. Docker Compose publishes both listener ports to host loopback by default; change those mappings when other LAN devices or a reverse proxy need to reach them.

See MCP Apps host support for protocol behavior, security guarantees, display modes, compatibility limits, and the versioned compliance matrix.

Run via npx (npm package)

npx flujo-ai

This runs a prebuilt FLUJO with no git clone or local build. Your data lives in ~/.flujo by default (override with FLUJO_DATA_DIR); the port defaults to 4200 (--port / FLUJO_PORT), and the browser opens automatically unless you pass --no-open. MCP servers may still need git, python/uv, or Node on your PATH. To update, just rerun with npx flujo-ai@latest. (The npm package is flujo-ai — the name flujo is blocked by npm's similarity rules — but the installed command is still flujo.)

One-line install (Windows)

On a fresh Windows machine you can install everything (Git, Node.js, Python, uv, ripgrep), clone FLUJO, build it, and optionally start it with a single PowerShell command:

irm https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.ps1 | iex

By default FLUJO is installed into %LOCALAPPDATA%\FLUJO. To customise the install without the interactive prompt, set environment variables first, e.g.:

$env:FLUJO_DIR = "D:\Apps\FLUJO"; $env:FLUJO_START = "1"; irm https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.ps1 | iex

See scripts/install.ps1 for all options.

Prefer a graphical installer? Download flujo-setup.exe from the latest release — it's a wizard around the same install.ps1 script above (see installer/flujo-setup.iss).

The Windows installer is a networked bootstrapper, not an offline file-copy package. It requires Windows App Installer (winget) and access to GitHub, the winget catalog, npm, and Python package sources. Missing Git, Node.js, Python, uv, and ripgrep are installed through winget; Ollama is optional. The installer also installs the Claude Code CLI used by the optional Claude Subscription provider. Running the installer again against an existing FLUJO Git checkout updates and rebuilds that checkout. For safety, an existing target that is not a Git checkout is rejected before registration or cloning.

Corporate proxy and custom CA

Both one-line installers and flujo-setup.exe are network bootstrappers. They require Node.js 22 or newer and may contact GitHub/raw.githubusercontent.com, the OS package manager, the npm registry, and Patchright 1.61.1's managed-browser mirrors at cdn.playwright.dev and playwright.download.prss.microsoft.com. Ask your network administrator to allow those services or provide an approved mirror.

Prefer your organization's approved OS trust configuration. If that is unavailable, set an explicit proxy and readable PEM CA bundle for the installer session. The FLUJO_* aliases are mapped only into installer child processes; they do not change global npm/Git configuration, the certificate store, or persistent environment variables.

Windows PowerShell:

$env:FLUJO_HTTPS_PROXY = "https://proxy-user:proxy-password@proxy.example.test:8443"
$env:FLUJO_NO_PROXY = "localhost,127.0.0.1,.example.test"
$env:FLUJO_EXTRA_CA_CERTS = "C:\Certificates\corporate-root.pem"
$env:FLUJO_PLAYWRIGHT_DOWNLOAD_CONNECTION_TIMEOUT = "120000"
irm https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.ps1 | iex

Linux/macOS:

export FLUJO_HTTPS_PROXY='https://proxy-user:proxy-password@proxy.example.test:8443'
export FLUJO_NO_PROXY='localhost,127.0.0.1,.example.test'
export FLUJO_EXTRA_CA_CERTS='/path/to/corporate-root.pem'
export FLUJO_PLAYWRIGHT_DOWNLOAD_CONNECTION_TIMEOUT='120000'
curl -fsSL https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.sh | bash

The initial irm/curl request must itself be able to reach GitHub, so configure the shell or OS proxy first if required. Optional FLUJO_HTTP_PROXY, FLUJO_PLAYWRIGHT_DOWNLOAD_HOST, and standard HTTP_PROXY/HTTPS_PROXY/NO_PROXY, NODE_EXTRA_CA_CERTS, npm_config_cafile, PLAYWRIGHT_DOWNLOAD_HOST, and PLAYWRIGHT_DOWNLOAD_CONNECTION_TIMEOUT values are also honored. Proxy URLs may contain credentials; do not paste them into issue reports. Installer logs redact known secret forms and are saved under the FLUJO CLI metadata directory.

Managed Chromium is installed as the named patchright-chromium stage. After correcting a proxy, CA, DNS, or timeout problem, retry only that version-matched browser download from the FLUJO directory:

node mcp-servers/browser/scripts/install-browser.mjs

On Ubuntu/Debian, the Unix installer also installs Chromium's Linux libraries and fonts in the patchright-system-dependencies stage, then checks a real headless browser launch in patchright-verification. After updating FLUJO, retry a failed browser setup from the FLUJO directory:

sudo "$(command -v node)" mcp-servers/browser/scripts/install-browser.mjs --install-deps
node mcp-servers/browser/scripts/install-browser.mjs --verify

The dependency step requires root (omit sudo when already root); browser verification runs as your regular user. Production builds use tsconfig.build.json to check application code; npm run typecheck still checks the full test suite.

Never use NODE_TLS_REJECT_UNAUTHORIZED=0, npm strict-ssl=false, or another TLS-verification bypass. The installers ignore an inherited Node TLS bypass and direct you to secure proxy/CA configuration instead.

One-line install (Linux / macOS)

The same for Linux and macOS — installs the prerequisites (Git, Node.js, Python, uv, ripgrep) via your package manager (or Homebrew on macOS), clones FLUJO, builds it, and registers the flujo command:

curl -fsSL https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.sh | bash

By default FLUJO is installed into ~/FLUJO. To customise without the interactive prompts, set environment variables first, e.g.:

curl -fsSL https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/install.sh | FLUJO_DIR="$HOME/apps/FLUJO" FLUJO_START=1 bash

See scripts/install.sh for all options.

Uninstalling (Windows)

To remove FLUJO, run the uninstaller:

irm https://raw.githubusercontent.com/mario-andreschak/FLUJO/main/scripts/uninstall.ps1 | iex

or, from inside your install folder:

powershell -ExecutionPolicy Bypass -File scripts\uninstall.ps1

It asks, per prerequisite (Git, Node.js, Python, uv, ripgrep, and optional Ollama), whether to remove it — defaulting to yes for ones FLUJO installed and no for ones that were already on your system — then removes the flujo command and the FLUJO folder. These ownership decisions come from %LOCALAPPDATA%\FLUJO-cli\install-manifest.json; without a readable manifest, all detected prerequisites default to keep. The graphical bootstrapper is intentionally not registered in Windows Apps, so this direct PowerShell command is the supported uninstall entry point.

⚠️ This permanently deletes your data. All workspace data—including flows, encrypted API keys, MCP server configs, chat history, user files and runtime artifacts—lives below \workspaces\\ and is removed with the installation/data folder. Use FLUJO's built-in backup/export first if you want to keep it.

Installs created before this feature have no manifest; the uninstaller then defaults every prerequisite to keep (it can't tell which FLUJO installed). Re-running the installer once writes the manifest for future uninstalls. See scripts/uninstall.ps1 for details.

📖 Usage

Saving API keys and shared values

  1. Open More → Settings → Global variables
  2. Save the API key or shared value once
  3. Bind that variable when configuring an AI or connected app

Connecting AI

  1. Open AI Setup
  2. Click Connect AI
  3. Choose the gentle guide, the faster guided path, or the expert form
  4. Select a provider, enter its credentials, and save the connection

Connecting Apps and MCP Servers

  1. Open Connected Apps
  2. Click Connect App
  3. Let AI help, browse curated apps, or provide a remote URL, GitHub repository, or local command
  4. Configure any required environment variables and test the connection
  5. Open the connected app to browse and test its tools, resources, and prompts

Building Agents

  1. Open Agents and create an agent
  2. Stay in Simple mode to add plain-language steps, or switch to Expert for the visual graph
  3. Connect an AI, apps, or other agents to each step
  4. Check the agent, save it, and click Try it

For branching, loops, and subflows, see Orchestration & Subflows above.

Automating Agents

  1. Go to More → Automations → Triggers
  2. Click "Add trigger" and choose a trigger: Schedule, Webhook, File Watch, MCP Tool Polling, or URL Watch
  3. Pick the agent or flow to run and configure the trigger-specific options
  4. Save — FLUJO runs it in the background while the app is open and keeps the run history on the Triggers page

Talking to an Agent

  1. Open Talk
  2. Select an agent
  3. Start chatting — enable the debugger or tool approvals from the input bar when you want more control over the run

📄 License

FLUJO is licensed under the MIT License.

🚀 Roadmap

Most of the original roadmap has shipped: MCP resources/prompts/roots/sampling, the MCP Marketplace & Spotlight, subflows, the visual debugger, and Automation triggers (scheduled/triggered headless runs) are all in. The main thing left on the list is AI-assisted flow generation — describe what you want and have FLUJO draft the flow for you.

Beyond that, ideas we're keeping an eye on:

  • Real-time voice input/output
  • Deeper MCP roots support (checkpoints/restore)
  • Edge-device-friendly builds

Have a feature request? Open a GitHub issue or drop it on Discord.

🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📬 Contact

Bonus: “A sad song about MCP”

FLUJO animated short: A sad song about MCP

Privacy & usage

FLUJO shares one anonymous daily-active pulse by default. The payload is limited to the app version, platform, install method, UTC date, and a random identifier that changes every day; it contains no flows, prompts, models, keys, filenames, account details, or permanent installation identifier. A daily in-app notice discloses the check. Sharing and the notice can be controlled independently under Settings → Privacy & Usage. Set FLUJO_TELEMETRY_URL to point at a self-hosted compatible collector.

Notes:

  • You can add ~FLUJO=HTML, ~FLUJO=MARKDOWN, ~FLUJO=JSON, ~FLUJO=TEXT in your message to format the response, this will give varying results in different tools where you integrate FLUJO.
  • You can add ~FLUJOEXPAND=1 or ~FLUJODEBUG=1 somewhere in your message to show more details
  • in config/features.ts you can change the Logging-level for the whole application

FLUJO - Empowering your AI workflows with open-source orchestration.

Ecosystem

MseeP.ai Security Assessment Badge Verified on MseeP

Frequently asked questions

Is FLUJO free to use?

FLUJO is open source under the MIT licence. There is no licence fee and no seat count — you can self-host it or, where the project offers one, pay a vendor for a managed version instead.

What does FLUJO do?

Multi-Agent + Automation: Workflows, Automation, Self-Improving Agents

What is FLUJO written in?

FLUJO is primarily written in TypeScript. Its source is publicly available at https://github.com/mario-andreschak/FLUJO, and it has 671 GitHub stars.