Floom

Name: Floom
Author: floomhq

by floomhqversion 0.1.6i★ –iRuns on your computer

Registry nameio.github.floomhq/floom

Install

Overview

Description from the maker (original English)

Deploy Python functions as web apps with auto-generated UI, REST API, and shareable links.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Developer tools
You need to fill in: FLOOM_BASE_URL, FLOOM_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: FLOOM_BASE_URL, FLOOM_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "floom": {
      "command": "npx",
      "args": [
        "-y",
        "@floomhq/mcp-server"
      ],
      "env": {
        "FLOOM_BASE_URL": "your-value",
        "FLOOM_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add floom --env FLOOM_BASE_URL=your-value --env FLOOM_API_KEY=your-value -- npx -y @floomhq/mcp-server

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "floom": {
      "command": "npx",
      "args": [
        "-y",
        "@floomhq/mcp-server"
      ],
      "env": {
        "FLOOM_BASE_URL": "your-value",
        "FLOOM_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "floom": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@floomhq/mcp-server"
      ],
      "env": {
        "FLOOM_BASE_URL": "your-value",
        "FLOOM_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

FLOOM_BASE_URL required env
Base URL of the Floom control plane
FLOOM_API_KEY secret required env
API key for authenticating with Floom

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account floomhq, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

More stars than 0% of the other 1390 servers in this category
Published to the registry more recently than 11% of the other 1390 servers in this category
Basic checks equal to or better than 100% of the other 1390 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Floom safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: FLOOM_BASE_URL, FLOOM_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.6) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Floom

The loop engineering harness. AI workers that run on a loop.

Schedule them, trigger them, require approvals, and keep every run on the record.

A worker is a folder: worker.yml + SKILL.md or run.py . Deploy it from Claude Code, Codex, or the CLI. Run it from the UI, REST, or MCP.

Get started · Build a worker · Try the hosted version · Read the docs

Most "AI automation" is a chat window you babysit, or a no-code graph that bills you per task and can't be audited. Floom is the loop engineering harness: a real runtime where a worker is a readable package, it runs on a loop without you watching, and every execution leaves logs, outputs, tool calls, approvals, and a replay you can trust. Used natively from Claude Code and Codex via MCP or CLI.

Deploy A Python Script As An App, REST API, And MCP Tool

Floom lets an agent or developer turn a Python script into a worker that non-developers can run from a UI, other systems can call through REST, and AI agents can operate through MCP.

Start with three files:

workers/my-worker/

worker.yml run.py requirements.txt

Then validate, deploy, and run:

floom workers validate ./workers/my-worker

floom workers push ./workers/my-worker floom run my-worker --input key=value

Read BUILDING.md for the full copy-paste worker contract.

What Floom Is: Worker Runtime For Background AI Workers

Floom turns repeatable knowledge-work automations into background AI workers. A worker can run manually, on a schedule, from a webhook, or from an app event. The runtime keeps the worker definition, input schema, output schema, logs, tool calls, approvals, and run history inspectable.

Use Floom when you want an AI agent to do recurring work without turning that work into an opaque chat thread, a hard-to-diff automation graph, or a one-off script with no supervision.

Build And Deploy An AI Worker From A Folder

AI agents and developers can build a Floom worker from a folder:

workers/<worker-id>/

worker.yml # manifest: inputs, outputs, trigger, runtime, secrets run.py # script entrypoint, or SKILL.md for agent mode requirements.txt # optional Python dependencies

Deploy the worker with:

floom workers validate ./workers/<worker-id>

floom workers push ./workers/ floom run --input key=value

After deployment, Floom exposes the worker in the UI, through REST endpoints, and through the Floom MCP server for AI clients. For the complete copy-paste build contract, read BUILDING.md.

What A Worker Looks Like

A worker is a folder-backed job definition. Describe the work in plain English (SKILL.md) or hand it a script (run.py), declare its tools, trigger, memory, and secrets in worker.yml, and Floom runs it.

# workers/github-digest/worker.yml  (abbreviated)

name: github-digest description: "Every morning at 9am, send a digest of unread GitHub PRs and open issues." exec: entry: SKILL.md # plain-English agent; or run.py for a script trigger: type: schedule cron: "0 9 * * *" # also: manual, webhook, Composio event connections:

app: github # the only tools this agent is allowed to call allowed_tools: [GITHUB_FIND_PULL_REQUESTS, GITHUB_LIST_ASSIGNED_ISSUES]

<!-- workers/github-digest/SKILL.md -->

You are a GitHub assistant generating a daily PR + issues digest. Fetch the user's open PRs and assigned issues, compile a markdown digest with Action items, and finish_with_outputs({ "digest": " " }).

It runs at 9am, calls only the two GitHub tools it declared, and writes digest.md to a run you can open, replay, or roll back:

run 7f3a · github-digest · finished 09:00:04 · 2 tool calls · output: digest.md

✓ GITHUB_FIND_PULL_REQUESTS q="is:open is:pr author:@me" → 4 PRs ✓ GITHUB_LIST_ASSIGNED_ISSUES state=open → 2 issues → out/digest.md (text/markdown) [open · replay · rollback]

The full manifest adds schema_version, title, version, and declared outputs. See workers/ for runnable examples, BUILDING.md for a minimal deployable worker, and the agent cookbook.

Two kinds of agent

	runs in	host isolation	tools	side effects
Script (`run.py` / `.sh` / `.js` / `.ts`)	E2B sandbox microVM	isolated filesystem, env & process; platform secrets withheld	sandbox + declared connections	approval gate when declared
Agent (`SKILL.md`)	AgentDriver in the API process (trusted bundles only)	not microVM-isolated by policy	declared connections, allow-listed	approval gate when declared

Sandboxes allow public network egress by default and block private/internal ranges; a stricter allowlist is optional. Full trust model: ARCHITECTURE.md.

Worker Runtime At A Glance


What it is	Self-hosted runtime to create, run, and supervise background AI agents
Best for	Recurring agent work: inbox triage, digests, outreach drafting, enrichment, monitoring
Agent types	Script (`run.py`/`.sh`/`.js`/`.ts`) and plain-English agent (`SKILL.md`)
Isolation	Script workers run in E2B sandbox microVMs - isolated host filesystem, env & process; platform secrets withheld
Triggers	Manual, schedule (cron), webhook, Composio event
Safety	Human-in-the-loop approvals for side-effecting agents; tools allow-listed per agent
On the record	Every run records logs, outputs, tool calls, approval state, replay + rollback
Cost model	Floom adds no per-task fee - you pay E2B sandbox runtime (per second) plus your model/API provider usage
Stack	Next.js + Tailwind UI · FastAPI + SQLite API · MCP server + CLI
Runs on	Linux, macOS, Windows (Python 3.11+, Node 20+)
License	MIT · hosted version

Who Floom Is For

Founders & operators turning recurring work (digests, triage, outreach) into agents that run themselves.
Engineers who want a real runtime - manifests, sandboxes, limits, approvals - not a prompt file and a cron job.
Teams who need every action allow-listed, approved, and replayable for audit.
Anyone burned by agents that ran a destructive command, leaked a secret, or claimed success with nothing on the record.

Floom Compared: Raw Scripts vs Zapier vs Hand-Rolled MCP

	raw scripts	Zapier / Make	hand-rolled MCP server	Floom
Worker definition	ad-hoc prompt or code	visual graph, hard to diff	custom tool server code	a folder: `worker.yml` + `SKILL.md` or `run.py`
Runtime	cron, shell, or local process	vendor automation runtime	whatever the developer builds	agent runtime with triggers, runs, logs, outputs, approvals, replay, and rollback
Isolation	runs on your host	vendor cloud, opaque	depends on implementation	E2B sandbox microVM for script workers
Tool access	whatever the script can reach	per-connector	MCP tools only	declared and allow-listed per worker
Side effects	fire immediately	workflow-dependent	custom approval logic	human approval gate when declared
Observability	scrollback, if any	per-step logs	custom logs	logs, tool calls, outputs, artifacts, approval state, replay, and rollback
Agent access	custom wrapper needed	not an agent-native build target	agent can call tools, but app runtime is separate	MCP tools let agents create, run, watch, and inspect workers
Cost model	model tokens and infrastructure	per-task or per-execution fees	model tokens and infrastructure	no per-task fee; you pay runtime and provider usage
Hosting	your host	vendor only	your host	self-host, or [hosted](https://floom.dev)

Quick Start: Run Floom Locally

Linux / macOS

git clone https://github.com/floomhq/floom.git

cd floom ./scripts/setup.sh

edit apps/api/.env: add a model provider key and E2B_API_KEY

./scripts/dev.sh

Windows PowerShell

git clone https://github.com/floomhq/floom.git; cd floom

.\scripts\setup.ps1

edit apps\api\.env: add a model provider key and E2B_API_KEY

.\scripts\dev.ps1

Requires Python 3.11+, Node.js 20+, Git, a model provider key, and an E2B key from e2b.dev. Open http://localhost:3000 and sign in - no auth secret for local dev, and the example agents are seeded on first boot.

Full setup, model providers, optional integrations, and the safe self-hosting checklist: docs/GETTING-STARTED.md. Common issues: docs/TROUBLESHOOTING.md.

Not ready to self-host? floom.dev is the hosted version - hire AI agents with no setup. Hosted users can start from an MCP client with:

npx -y @floomhq/floom mcp install --target claude

The .env, model-provider, and E2B keys above are for running your own local or self-hosted runtime, not for using Floom Cloud.

How a run works

Core concepts

Agents - folders under workers/ / with worker.yml plus a script entrypoint (run.py) or an agent prompt (SKILL.md).
Runs - every execution records logs, outputs, tool calls, approval state, and replay/rollback context.
Contexts - reusable file bundles attached to agents as reference material; sensitive by default.
Approvals - side-effecting agents pause for a human decision before anything leaves the building.
Workspace history - agents, contexts, and settings versioned in a git-backed workspace for rollback.

Write your first agent in docs/GETTING-STARTED.md, then docs/AUTHORING.md for the full manifest and runtime contract.

How workers execute

Script workers (.py/.sh/.js/.ts) run in an E2B sandbox microVM by default: isolated dependencies, no host process access, contained resources. TypeScript workers use the Node runtime with tsx (npx --yes tsx run.ts) and the same inputs.json/result.json contract as Python workers. A bundle that dumps os.environ inside the sandbox sees only sandbox metadata - FLOOM_SECRET, provider keys, and E2B_API_KEY are all absent. Agent workers (SKILL.md) run through the API-hosted AgentDriver tool loop and are governed by their declared connections an

Only the beginning is shown; read the rest in the repo

Floom

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Developer toolsi

Common questions

Alternatives

GitHub

Desktop Commander

Cloudflare MCP

README from the maker

Deploy A Python Script As An App, REST API, And MCP Tool

What Floom Is: Worker Runtime For Background AI Workers

Build And Deploy An AI Worker From A Folder

What A Worker Looks Like

Two kinds of agent

Worker Runtime At A Glance

Who Floom Is For

Floom Compared: Raw Scripts vs Zapier vs Hand-Rolled MCP

Quick Start: Run Floom Locally

edit apps/api/.env: add a model provider key and E2B_API_KEY

edit apps\api\.env: add a model provider key and E2B_API_KEY

How a run works

Core concepts

How workers execute