# Gumloop — No-code platform for building, sharing and governing AI agents that work across a company's apps and data.

> Source: The Agents Index — https://theagentsindex.com/gumloop (structured, researched, re-verified)
> Facts last verified: 2026-09-09

Gumloop is a no-code platform for building AI agents that use a company's own apps, data and models to complete work. Anyone in the business can build one, while IT keeps control of models, connectors and spend.

| Fact | Value |
| --- | --- |
| Website | https://www.gumloop.com |
| Price | from $37/month |
| Free trial | No |

No standing $0 plan: the only free route is a 14-day free trial of Pro that requires a card, is one-time per customer, and converts to a paid Pro subscription unless cancelled.

## What it does

**Writes code** · Partly — Agents write and execute Python and shell in a per-chat cloud sandbox, and can commit files through the GitHub connector, but this is task scripting rather than repository-scale software authoring.

> The Code Sandbox gives your agent the ability to execute Python code and shell commands in a secure, isolated cloud environment.
> — https://docs.gumloop.com/core-concepts/agent_sandbox_and_secrets · Code Sandbox & Secrets, opening paragraph

**Reviews code** · Partly — Through the GitHub connector an agent can open a pull request's changed files and inline review comments and post its own comment, but there is no dedicated review product or verdict workflow.

> List inline review comments on a PR (code-level comments on specific lines/files)
> — https://docs.gumloop.com/nodes/mcp/github · GitHub connector page, Available Tools table, List Pull Request Review Comments row

**Ships it** · Partly — Gumloop builds and deploys custom MCP servers straight from a GitHub repository on every push to main, but that ships the connector code, not the buyer's own applications.

> You write the code in a GitHub repository, and Gumloop handles building, deploying, monitoring, and routing requests to your server.
> — https://docs.gumloop.com/enterprise-features/hosted_mcps · Hosted MCPs, opening paragraph

**Done-for-you service** · No — You buy self-serve software and build the agents yourself; the only vendor-people option is an optional Embedded Gumloop Expert on Enterprise, which the plan table lists as support, not delivery.

> Gumloop is an AI agent platform. Build AI agents that use your tools and data to do real work, then automate them with triggers, schedules, and the API.
> — https://docs.gumloop.com/ · Welcome to Gumloop, page description

_Not established: Debugs and fixes_

## How much it does unattended

**Runs autonomously** · Yes — Scheduled, app and webhook triggers run agents unattended with no chat window open, and approval gates are opt-in per tool rather than mandatory.

> Agents can run autonomously without manual interaction.
> — https://docs.gumloop.com/core-concepts/agent_triggers · Agent Triggers, opening paragraph

**Multi-agent** · Yes — An agent can clone itself to parallelise research or hand work to named specialist agents, each running in its own conversation and sandbox.

> Skills teach this agent how to do a job. Subagents are other agents you hand work to.
> — https://docs.gumloop.com/help/skills-triggers-mcp/skills-vs-subagents · Skills vs Subagents, opening line

**Agent permissions** · Yes — Per-app presets (always allow, ask each time, ask for writes and deletes, custom), per-tool never-allow, and CEL rules on the actual arguments decide what runs before it asks.

> The agent never executes a gated tool call without your explicit go-ahead.
> — https://docs.gumloop.com/core-concepts/human_in_the_loop · Human in the Loop, How It Works section

## Which models it runs on

**Claude** · Yes — Anthropic models are selectable per agent and through the completions endpoint; the one Anthropic family with 30-day retention stays blocked until an admin acknowledges it.

> OpenAI-compatible chat completions endpoint, multiplexed across every model Gumloop supports (Anthropic, OpenAI, Google Gemini, OpenRouter routes).
> — https://docs.gumloop.com/api-reference/chat-completions/create-completion · Create chat completion, endpoint description

**GPT** · Yes — OpenAI is one of the providers you can browse in the agent model picker, and its models are also reachable through the OpenAI-compatible completions API.

> To pick a specific model instead, search by name or browse by provider: Anthropic, OpenAI, Google, DeepSeek, MiniMax, Z.ai, and more.
> — https://docs.gumloop.com/core-concepts/ai_models · AI Models, Choosing a model section

**Open models** · Yes — Open-weight models from DeepSeek, Z.ai, MiniMax and others run as agents, and Gumloop markets them as the cheaper default rather than a fallback.

> Each model is open weight and available to run as an agent in Gumloop.
> — https://www.gumloop.com/open-source-ai-models · The best open source LLMs, section introduction

**Model choice** · Yes — You pin the model per agent from 35 or more options or hand routing to Auto; Enterprise admins can restrict the list and point presets elsewhere.

> You choose the model in Agent Preferences, at the top of the agent's configuration.
> — https://docs.gumloop.com/core-concepts/ai_models · AI Models, opening paragraph

## Where you use it

**In your editor** · Partly — There is no Gumloop editor extension; IDEs reach it as MCP clients, so Cursor or VS Code drive Gumloop agents rather than hosting them in the editor.

> Connect to the Gumloop MCP server from Claude, Cursor, VS Code, and other MCP-compatible clients.
> — https://docs.gumloop.com/mcp-server/overview · MCP Server, page description

**On the command line** · Yes — A macOS and Linux CLI with a JSON mode covers agents, sessions, chat, MCP tools and artifacts; native Windows is unsupported and needs WSL or the SDK.

> gumloop is the command line for Gumloop. Sign in once, then drive your agents, sessions, chat completions, MCP integrations, Company Brain, skills, and artifacts from the terminal.
> — https://docs.gumloop.com/cli/overview · Gumloop for Terminal, opening paragraph

**In your pipeline** · Partly — Webhook triggers and a scriptable CLI let CI jobs or cron start an agent, but Gumloop ships no pull-request check, CI app or build-status integration of its own.

> Anything that can send an HTTP POST — Stripe, GitHub, a cron job, an internal script — runs the agent by calling it.
> — https://docs.gumloop.com/api-reference/getting-started · Getting Started, Agent Webhooks section

**In a browser** · Yes — Agents are built and chatted with in the gumloop.com web app, and any agent can also be published as a standalone hosted chat page for other people.

> Hosted Pages let you publish your agent on a dedicated URL at gumloopagents.com.
> — https://docs.gumloop.com/core-concepts/hosted_pages · Hosted Pages, opening paragraph

## Whose machine it runs on

**Self-hosted** · Partly — Running Gumloop on your own infrastructure is an Enterprise VPC option that the plan table marks Optional; Pro is vendor-hosted with no self-run path.

> Enterprise customers running Gumloop in their own VPC are not charged for compute at all, since it runs on their infrastructure.
> — https://docs.gumloop.com/core-concepts/credits · Credits, Compute accordion

_Not established: Open source_

## What it costs to run

**How it meters** · Yes — Metering is per credit at $0.005: model tokens at provider cost, one credit per successful tool call, five credits per session-minute, plus an eight per cent orchestration fee.

> Credits are the currency that powers Gumloop. Every agent conversation spends credits based on the AI model it uses, the tools it calls, and how long it runs.
> — https://docs.gumloop.com/core-concepts/credits · Credits, opening paragraph

**Free tier** · Partly — You can sign up without talking to sales, but the only free route is a card-backed 14-day Pro trial that converts to paid; no standing zero-dollar plan is offered.

> Every new account starts with a 14-day free trial of Pro. The trial requires a card, is a one-time offer per customer
> — https://docs.gumloop.com/core-concepts/credits · Credits, Plans and included credits section

**API access** · Yes — A REST API with key or bearer auth, unauthenticated webhook trigger URLs, and Python and JavaScript SDKs cover agent creation, sessions and completions on both plans.

> The Gumloop API is agent-first: you can create and update agents, start sessions to chat with them, and use chat completions from any OpenAI-compatible client.
> — https://docs.gumloop.com/api-reference/getting-started · Getting Started, opening paragraph

**MCP server** · Yes — A remote MCP server lets another AI client list, create and run Gumloop agents, and the plan table checks Gumloop MCP for both Pro and Enterprise.

> Gumloop exposes a remote Model Context Protocol (MCP) server that lets any compatible AI client manage your agents, sessions, skills, and more.
> — https://docs.gumloop.com/mcp-server/overview · MCP Server, opening paragraph

**Bring your own key** · Yes — Your own provider keys are accepted on both plans and zero the token charge, but the orchestration fee doubles to sixteen per cent of the notional list cost.

> the credits that would have been allocated toward the cost of tokens drop to zero, and the orchestration fee increases from 8% to 16%
> — https://www.gumloop.com/pricing · Frequently asked questions, 'Can I bring my own API key(s)?' answer, expanded in the browser

## Buying it for a team

**A company can buy it** · Yes — An organisation account holds billing, users and security, with unlimited seats and teams on Pro and a sales-quoted contract on Enterprise.

> Your company's account that manages billing, users, and security
> — https://docs.gumloop.com/core-concepts/teams · Organization and Teams, At a Glance, Organization card

**Seat model** · No — Gumloop is not sold per seat: the plan table lists unlimited seats and teams on both tiers, so cost tracks credit consumption rather than headcount.

> Unlimited
> — https://www.gumloop.com/pricing · Plan comparison table, Collaboration section, Seats row, Pro column

**Pooled budget** · Yes — One organisation-wide credit pool funds every member's agents, and an API endpoint lets admins set a monthly credit limit per custom role on top of it.

> Everyone in your organization shares the same credit pool.
> — https://docs.gumloop.com/core-concepts/teams · Organization and Teams, At a Glance tip

**Admin controls** · Partly — Anyone can gate their own agent's tool calls, but organisation-wide app policies, role-based access and model restrictions are Enterprise-only, so Pro governance stops at the agent.

> App Policies is an Enterprise feature.
> — https://docs.gumloop.com/enterprise-features/app-policies/overview · App Policies, Who can use it warning

**Audit log** · Partly — Audit logs record sign-ins, credential access and organisation changes, but the plan table checks the row only for Enterprise, so Pro has no administrative trail.

> Audit Logging provides comprehensive tracking and monitoring of user actions across your Gumloop organization.
> — https://docs.gumloop.com/enterprise-features/audit_logging · Audit Logging, opening paragraph

**Single sign-on** · Partly — SAML single sign-on and SCIM provisioning with Okta, Entra, Google, JumpCloud and Ping require Enterprise; Pro members sign in with Google, Microsoft or a password.

> SAML and SCIM settings require the Admin organization role and an Enterprise subscription.
> — https://docs.gumloop.com/enterprise-features/sso_saml_scim · SAML Configuration, Setting Up SAML, Access SSO Settings note

## What happens to your code

**Opt out of training** · Yes — Third-party models run under zero-data-retention agreements by default, and the one family that retains prompts for thirty days stays blocked until an admin explicitly acknowledges it.

> Every model Gumloop serves runs under Zero Data Retention except Anthropic's Claude Fable family, where Anthropic keeps prompts and outputs for 30 days to check for misuse, then deletes them.
> — https://docs.gumloop.com/enterprise-features/ai_model_control · AI Model Governance & Configuration, Models with 30-day data retention

**Data residency** · Partly — Jurisdiction is only controllable on Enterprise by deploying into your own cloud account; the hosted service publishes no region choice, and its outbound traffic egresses from Oregon.

> Deploy Gumloop inside your own AWS, Azure, or Google Cloud environment to keep data in your network.
> — https://www.gumloop.com/ · Enterprise-grade controls section, VPC deployments card

**Getting out** · Partly — Bulk export of runs, agents and audit logs is an Enterprise admin feature; everyone can pull artifacts and skills through the CLI, and Pro's monthly credits expire unused.

> Usage Data Export allows enterprise organization administrators to export comprehensive data from their Gumloop organization.
> — https://docs.gumloop.com/enterprise-features/organization_data_export · Usage Data Export, opening paragraph

**Certifications** · Yes — The vendor claims an independently audited SOC 2 Type II, and its trust centre lists SOC 2 Type 2, GDPR and HIPAA as compliant with reports available on request.

> SOC 2 Type II. Independently audited and compliant.
> — https://www.gumloop.com/ · Enterprise-grade controls section, SOC 2 Type II card

## Provenance

Every fact above comes from the vendor. Nothing here is independently corroborated yet.

## Coverage elsewhere

None recorded. Every fact above comes from the vendor and is not independently corroborated yet.

## What changed

- 2026-09-09 — Capabilities · Commercial terms · Free tier · Price

## Correcting this record

Anything marked "Not established" is a question we have not answered — it is not a No. If you represent Gumloop, or anything here is wrong or out of date, you can supply it with a source: the operations this site accepts from an agent are listed at https://theagentsindex.com/.well-known/agents.json — that catalogue needs no key to read, and each entry states its own auth.

Supplying evidence is free. Nothing that can be bought here changes what a field says, whether a gap is closed, or how this record is scored.