Open-source alternatives to Zapier: 4 workflow automation tools compared
Replacing Zapier with self-hosted software moves the cost from task runs to servers you run yourself, and the four tools here make very different trades for that. Most readers should start with n8n-io/n8n, while windmill-labs/windmill fits teams whose automation is code rather than something they click together.
What Zapier does, and why people look elsewhere
Zapier connects web apps through hosted, no-code workflows: a trigger in one service runs actions in others.
- billing by the number of task runs, so a busy workflow gets expensive
- workflows and credentials for every connected service sit on Zapier's servers
- no way to run a workflow on your own infrastructure or next to a private database
The candidates at a glance
| Project | Licence | Maintenance | Language | GitHub stars | Install | Best for |
|---|---|---|---|---|---|---|
| n8n-io/n8n | Custom licenceCustom licence: read the LICENSE file | Commits in the last six monthsLast push October 8, 2026 | TypeScript | 206,717 | See analysis | You want the same shape of app to app automation as Zapier, but running on your own machines, with a canvas that drops into JavaScript or Python when a flow outgrows node clicking. It is the closest fit when the workflows stay inside the company. |
| activepieces/activepieces | Custom licenceCustom licence: read the LICENSE file | Commits in the last dayLast push October 11, 2026 | TypeScript | 25,000 | See analysis | You want an open builder where the integration library is readable source and installable from npm, and you want that library exposed to LLM clients as MCP servers. It also fits teams that need to fork a single piece and patch it themselves. |
| windmill-labs/windmill | Custom licenceCustom licence: read the LICENSE file | Commits in the last dayLast push October 11, 2026 | Rust | 18,162 | See analysis | You already run Postgres and your automation is scripts. Windmill turns Python, TypeScript, Go or Bash into webhooks, schedules, flows and autogenerated UIs, which suits a team that wants code review on automation rather than a canvas nobody outside the team can edit. |
| huginn/huginn | MITPermissive: commercial use allowed | Commits in the last six monthsLast push October 10, 2026 | Ruby | 50,041 | See analysis | You want the IFTTT shape: agents that watch a source, emit events and pass them along a directed graph, on a server you control. It fits long lived monitoring and notification jobs better than transactional business flows with many service specific steps. |
Each alternative in detail
n8n-io/n8nA fair-code workflow automation platform with native AI capabilities.
- Best for
- You want the same shape of app to app automation as Zapier, but running on your own machines, with a canvas that drops into JavaScript or Python when a flow outgrows node clicking. It is the closest fit when the workflows stay inside the company.
- What you give up
- The licence is the part most teams underestimate: the community build runs under the Sustainable Use License and other features under the n8n Enterprise License, so reselling automation as a hosted feature to customers is outside what the default grant covers, and someone has to read LICENSE.md and LICENSE_EE.md to classify it at all. Operationally you inherit a persistent Docker volume of workflows, credentials and execution history, and any version you pin has to still be receiving releases after the 2026-08-28 build.
activepieces/activepiecesAI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
- Best for
- You want an open builder where the integration library is readable source and installable from npm, and you want that library exposed to LLM clients as MCP servers. It also fits teams that need to fork a single piece and patch it themselves.
- What you give up
- The MIT grant covers the community build while enterprise features ship under a commercial licence, so an embedded builder or multi-tenancy plan has to be checked against that boundary before you build on it. Sandboxed code steps reach for Linux kernel capabilities through libcap2, so a restricted Kubernetes cluster needs AP_EXECUTION_MODE tested before production. The piece catalogue is also smaller than n8n's, and there is no single install command in our analysis, so the deployment is documentation you assemble rather than a recipe you copy.
windmill-labs/windmillOpen-source developer platform to power your entire infra and turn scripts into webhooks, workflows and UIs. Fastest workflow engine (13x vs Airflow). Open-source alternative to Retool and Temporal.
- Best for
- You already run Postgres and your automation is scripts. Windmill turns Python, TypeScript, Go or Bash into webhooks, schedules, flows and autogenerated UIs, which suits a team that wants code review on automation rather than a canvas nobody outside the team can edit.
- What you give up
- It is not a trigger and action tool. The unit of work is a script with typed parameters, so anything that needs a prebuilt app connector is code you write or something you take from the community hub. The deployment is Postgres-centric by design, with the docker-compose.yml db service and DATABASE_URL pointing at a database you operate and upgrade yourself, and AGPLv3 is a blocker for distribution models that ship a modified version.
huginn/huginnCreate agents that monitor and act on your behalf. Your agents are standing by!
- Best for
- You want the IFTTT shape: agents that watch a source, emit events and pass them along a directed graph, on a server you control. It fits long lived monitoring and notification jobs better than transactional business flows with many service specific steps.
- What you give up
- It is a Ruby on Rails application, so you are committing to a Rails deployment with MySQL or PostgreSQL behind it, and our analysis of huginn notes that the database adapter choice has to match the commands you run. The README points at the wiki rather than walking through production email, queueing and backup configuration, so that work lands on you. Release cadence is uneven too, with the second most recent tag in the list dated 2022-08-18 while the last push was 2026-09-26.
Four different shapes of automation, and the tools that are not here
Zapier is one idea: a trigger in one service runs actions in others, and the vendor hosts the whole thing. The four projects below solve that in four different ways, and only some of them are trying to be the same product.
n8n-io/n8n is the closest match. It ships a visual canvas with more than 1500 integrations, and it lets you drop into JavaScript, Python or npm packages when a flow outgrows node clicking. activepieces/activepieces is also a canvas, but the difference sits in the library: pieces are TypeScript packages published to npm, and the README states that every piece is also available as an MCP server.
windmill-labs/windmill starts from a script rather than a trigger. A function in Python, TypeScript, Go or Bash has its parameters parsed, gets a frontend generated for it, and can be chained into a flow or triggered by a schedule, webhook, HTTP route, Kafka topic, WebSocket or email. huginn/huginn is the oldest idea here: agents that watch a source, create and consume events, and propagate them along a directed graph. That is closer to a monitoring system than to a business process tool.
That leaves the obvious question. Why are Make and IFTTT missing? Both are hosted commercial services, which is the condition most readers here are trying to leave. They stay reasonable choices when nobody wants to run a server, and this page is not an argument against them. Also absent is the long tail of other hosted workflow products, and the trigger heavy glue scripts people write themselves. Neither group fixes the two things that send people looking: billing that scales with how much your workflows do, and workflows plus credentials sitting on someone else's servers.
Choosing by scenario: one person, a small team, a company under audit, a product team
Read the four as four answers to the question of who runs this.
One person with a handful of flows gets the most out of activepieces/activepieces or n8n-io/n8n, because a canvas removes the need to host anything heavier than a single container. If that person also wants their flows reachable from an LLM client, activepieces has the clearer answer: its README states that contributed pieces become automatically available as MCP servers usable through Claude Desktop, Cursor or Windsurf. n8n points at AI from the other direction, describing multi-step agents and AI workflows with model choice left open across OpenAI, Anthropic, Google or open source models.
A small team usually lands on n8n. More than 1500 integrations cover more of the SaaS a team already runs, and the 9,000+ workflow templates the README links are a starting point instead of a blank canvas. The price of that coverage is the licence question and a database you now own.
A company with compliance needs is the hardest case, and the requirement that workflows and credentials stay on your own infrastructure is the reason for the whole page. All four can do that. What separates them is the licence. MIT and AGPLv3 are categories a legal team recognises on sight. The Sustainable Use License, and a repository that splits an MIT community build from commercially licensed enterprise features, are not, and someone will have to read the files before the first workflow moves.
A team embedding automation into its own product is where windmill-labs/windmill earns its slot. It is built for internal code rather than for connecting a fixed list of third party apps, and the autogenerated UIs are a way to expose your own scripts to colleagues who do not write code.
What each one costs to keep running
Self-hosting is not one cost. It is four different shapes of it, and the install commands on this page are the first hint of which.
For n8n the documented path starts with a single Docker volume creation followed by a container run, and the project is designed around that. What you inherit is a persistent volume holding workflows, credentials and execution history, plus upgrades you have to rehearse, because pinning a version is normal practice and a pinned build has to still be receiving releases after the 2026-08-28 version.
windmill-labs/windmill is heavier and more explicit. The deployment is Postgres-centric by design: our analysis points at the docker-compose.yml db service and the DATABASE_URL setting, which means the database is not optional and its upgrades belong to you. The pip install wmill command on this page installs the Python client rather than the server, which is a fair signal about the size of the job.
activepieces/activepieces has no single install command recorded in our analysis, so treat the deployment as documentation you assemble rather than a recipe you copy. The part worth testing early is AP_EXECUTION_MODE, because sandboxed code steps reach for Linux kernel capabilities through libcap2 and a hardened Kubernetes cluster can refuse.
huginn/huginn is a Ruby on Rails application that needs MySQL or PostgreSQL, an APP_SECRET_TOKEN generated rather than copied from the example file, and a chosen upgrade path. The README sends you to the wiki instead of walking through production email, queueing and backups, so plan that work yourself.
What the licences mean when a company reads them
Two of these four are open source in a sense a legal team accepts at a glance, and two are not.
huginn/huginn is MIT, which means you can read it, run it, change it and host the result for internal use without a separate agreement. activepieces publishes its community build under MIT and keeps enterprise features under a commercial licence, so the boundary between the two is the thing to map against your plans, especially if you need an embedded builder or multi-tenancy.
windmill-labs/windmill is AGPLv3. That is comfortable for internal use and awkward when you distribute a modified version, because the copyleft obligation travels with what you hand out. The README states the project is fully open-sourced under AGPLv3 and that separate commercial licences are offered.
n8n-io/n8n is the case that surprises people most often. Its README describes the project as fair-code distributed under the Sustainable Use License and the n8n Enterprise License, with visible source and the right to self-host and extend. Our analysis of n8n is blunt about where that stops: if you intend to resell automation as a hosted feature to customers, the default grant is not the one you want. Read LICENSE.md and LICENSE_EE.md before committing. If your use is internal only, the Sustainable Use License is a workable answer, and that is the most common case.
MCP and agents are becoming a second axis
Two of the four treat LLM clients as a first class consumer, and that changes who they are for.
activepieces/activepieces publishes pieces as MCP servers, so a flow built for a colleague can also be driven from Claude Desktop, Cursor or Windsurf. The same integration library serves a human builder and a model, which is a real difference from a tool built only around a visual canvas.
n8n-io/n8n comes at the same thing from the builder side. Its README frames the product as a platform for AI agents and workflows, with tool use, human approvals and full observability described as production features rather than experiments.
windmill-labs/windmill and huginn/huginn do not claim this. Windmill is a developer platform for scripts, jobs, flows and UIs. Huginn is an event graph. If your reason for automating is to let a model call a tool inside a boundary you control, the first two are the ones to evaluate. If your reason is to move a record from one system to another on a schedule, the choice comes back to scenario and licence.
Bottom line
If your workflows are Zapier shaped and internal, start with n8n and read its two licence files before anything else; if your automation is code, windmill; if you want a readable npm library with MCP access, activepieces; if you want a long lived event graph, huginn. Before committing, run the install path on your own infrastructure, confirm the version you pin still receives releases, and have someone read the licence.