Open-source, self-hostable workflow automation platform with AI workflows, TypeScript pieces, human-in-the-loop steps, and a built-in MCP server.
Open the source and read safety notes before installing.
Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.
Decision playbook
Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.
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No baseline selected
No major trust-signal divergence detected in the current selection.
Confirm ownership and provenance before trusting install instructions.
Source link availableRequired
Open the canonical repository and verify ownership.
Source provenance statusRequired
Marked as source-backed.
Metadata reviewed
Registry metadata indicates a reviewed listing.
Validate risk disclosures before installation or API wiring.
Safety notes presentRequired
Review the listed safety guidance before running commands.
Privacy notes presentRequired
Review data handling notes before connecting accounts or secrets.
Trust level risk gateRequired
Trust level does not block evaluation.
Check package metadata and artifact integrity signals.
Install payload available
Install or copy payload is available for review.
Package verification flag
No package verification flag provided.
Checksum metadata
No checksum provided for downloaded artifact.
Use compare context to validate trade-offs before adoption.
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Baseline comparison available
No baseline peer selected yet.
Diverging trust signals identified
No major trust-signal divergence found.
Setup at a glance
Copy-ready — paste the snippet to get started.
Adoption plan
Current risk score 16/100. Use staged verification before broader rollout.
Validate source and review signals before any execution.
Confirm source provenanceRequired
Source URL/provenance metadata is present.
Confirm metadata review state
Listing has review metadata.
Verify install payload
Install/config payload exists and can be inspected.
Confirm safety, privacy, and package integrity signals.
Review safety notesRequired
Safety notes are present.
Review privacy notesRequired
Privacy notes are present.
Verify package integrity metadata
No package verification/checksum metadata.
Adopt in controlled steps based on the selected plan.
Run in isolated sandbox firstRequired
Use a constrained sandbox and observe behavior across multiple tasks.
Roll out graduallyRequired
Roll out to a small cohort before wider usage.
Set monitoring and fallback
Define rollback path and monitor errors after adoption.
Evidence readiness
Required evidence gates are covered (5/6 signals complete).
Source repository/provenance is listed.
Required in this preset
Review metadata is present.
Required in this preset
Safety notes are present.
Required in this preset
Privacy notes are present.
Optional in this preset
Package integrity metadata is missing.
Optional in this preset
Install payload is available.
Required in this preset
Required evidence gates are covered for this preset.
Decision timeline
5/6 steps complete with no blocking gaps for this preset.
triage
Source/provenance metadata is available.
triage
Review metadata is available.
verify
Safety notes are available.
verify
Privacy notes are available.
verify
Package integrity metadata is missing.
rollout
Install payload is available.
No required blockers for this timeline preset.
Prerequisite readiness
3 prerequisites to line up before setup. Have accounts and credentials ready first. Includes a review or approval gate.
Safety & privacy surface
3 safety and 3 privacy notes across 3 risk areas. Review closely: credentials & tokens, permissions & scopes, network access.
Disclosure: editorial
## Editorial notes
Activepieces is useful for teams that want a self-hostable automation layer between Claude-adjacent agents and business systems without routing everything through a closed automation platform. It combines a visual flow builder, open-source TypeScript pieces, AI workflow support, human-in-the-loop steps, self-hosting options, and a built-in MCP server that can expose approved automation capabilities to Claude Desktop, Cursor, Windsurf, or Claude.ai connectors.
## Source notes
- The official docs describe Activepieces as an open-source all-in-one automation tool with AI-ready flows, TypeScript pieces, enterprise customization, self-hosted/network-gapped deployment, and human-in-the-loop steps.
- The installation overview says Activepieces Community Edition can be deployed with Docker, Docker Compose, and Kubernetes, and that Community Edition is free and open source.
- The MCP Server docs describe a built-in MCP server that lets AI assistants build flows, manage tables, test automations, inspect runs, and use OAuth-authenticated project-scoped tools.
- The GitHub repository describes Activepieces as an open-source replacement for Zapier, an AI automation platform with TypeScript pieces, MCP support for pieces, AI-first workflow features, and MIT-licensed Community Edition code with commercial enterprise features.
## Duplicate check
Checked current `content/tools/`, `content/mcp/`, guides, skills, agents, open pull requests, live HeyClaude `llms-full.txt`, and repository-wide content for `Activepieces`, `activepieces.com`, `github.com/activepieces/activepieces`, `workflow automation`, `Zapier`, `Make`, `n8n`, `Pipedream`, `Workato`, and `Windmill`. Existing n8n, Make, Pipedream, Workato, Zapier AI, Zapier MCP, and Workato MCP entries cover adjacent automation platforms or MCP connectors, but no Activepieces tools entry, Activepieces source URL duplicate, or open duplicate PR was found.
## Disclosure
Editorial listing. No paid placement or affiliate link is used.Activepieces is useful for teams that want a self-hostable automation layer between Claude-adjacent agents and business systems without routing everything through a closed automation platform. It combines a visual flow builder, open-source TypeScript pieces, AI workflow support, human-in-the-loop steps, self-hosting options, and a built-in MCP server that can expose approved automation capabilities to Claude Desktop, Cursor, Windsurf, or Claude.ai connectors.
Checked current content/tools/, content/mcp/, guides, skills, agents, open pull requests, live HeyClaude llms-full.txt, and repository-wide content for Activepieces, activepieces.com, github.com/activepieces/activepieces, workflow automation, Zapier, Make, n8n, Pipedream, Workato, and Windmill. Existing n8n, Make, Pipedream, Workato, Zapier AI, Zapier MCP, and Workato MCP entries cover adjacent automation platforms or MCP connectors, but no Activepieces tools entry, Activepieces source URL duplicate, or open duplicate PR was found.
Editorial listing. No paid placement or affiliate link is used.
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[](https://heyclau.de/entry/tools/activepieces)Activepieces side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.
1 trust signal differ across this comparison (Submitter).
| Field | Open-source, self-hostable workflow automation platform with AI workflows, TypeScript pieces, human-in-the-loop steps, and a built-in MCP server. Open dossier | Visual automation platform for building integrations, scenarios, API workflows, and AI-connected business processes. Open dossier | Source-available workflow automation platform for self-hosted integrations, AI workflows, triggers, and data pipelines. Open dossier | Open-source SDK and runtime for building, running, and managing agent platforms with agents, teams, workflows, memory, knowledge, tools, MCP, and AgentOS. Open dossier |
|---|---|---|---|---|
| Next steps | ||||
| Trust | ||||
| Review status | ReviewedMaintainer reviewed | ReviewedMaintainer reviewed | ReviewedMaintainer reviewed | ReviewedMaintainer reviewed |
| Package trust | Package not verified | Package not verified | Package not verified | Package not verified |
| Source provenance | Source-backed | Source-backed | Source-backed | Source-backed |
| SubmitterDiffers | oktofeesh1 | — | — | oktofeesh1 |
| Install risk | Review first | Review first | Review first | Review first |
| Notes | Safety ✓ Privacy ✓ | Safety · Privacy · | Safety · Privacy · | Safety ✓ Privacy ✓ |
| Brand | ||||
| Category | tools | tools | tools | tools |
| Source | Source-backed | Source-backed | Source-backed | Source-backed |
| Author | Activepieces | Make | n8n | Agno |
| Added | 2026-06-03 | 2026-04-27 | 2026-04-27 | 2026-06-03 |
| Platforms | ||||
| Harness | ||||
| Source repo | 22.8k repo stars | — | — | — |
| Safety notes | ✓Activepieces flows can send messages, call APIs, write records, publish webhooks, run code, and trigger cross-system side effects, so production flows need tests, approvals, rollback paths, and rate-limit controls. The built-in MCP server can let AI assistants build flows, manage tables, inspect runs, test automations, and publish changes; enable only the needed tool categories and keep project scope tight. Custom TypeScript pieces and code steps should be reviewed like application code, especially when they handle secrets, filesystem access, network calls, or business-critical integrations. | — missing | — missing | ✓Agno agents are stateful control loops around stateless models, so model reasoning, tool calls, memory, knowledge retrieval, and workflow steps still require review before production use. Agents, teams, workflows, MCP tools, schedulers, and AgentOS APIs can call external systems, update databases, create memory, trigger background work, and expose capabilities to users or other agents. Agent memory and knowledge can make behavior more useful, but they can also preserve stale, incorrect, over-broad, or sensitive facts that influence future responses and actions. Human-in-the-loop approval, guardrails, tracing, RBAC, audit logs, and rollback paths should be configured before connecting Agno to billing, support, production data, infrastructure, or customer operations. MCP integrations discover tool schemas and let agents call third-party or internal services; review tool names, descriptions, arguments, auth headers, and permission scope before enabling them. Telemetry, tracing, evals, and AgentOS dashboards are operational signals, not proof that an agent platform is safe, compliant, accurate, or production-ready. |
| Privacy notes | ✓Workflows can process prompts, customer records, emails, documents, form responses, table data, app payloads, webhooks, run logs, error traces, and AI-generated outputs. Activepieces connections may store OAuth tokens, API keys, account identifiers, webhook URLs, and service credentials; avoid exposing them in prompts, logs, MCP tool output, screenshots, or exported flows. Self-hosted deployments still need retention, backup, database, Redis, worker isolation, outbound network, telemetry, and access-control policies for all flow and run data. | — missing | — missing | ✓Agno agents can process prompts, messages, tool arguments, tool results, retrieved knowledge, memory content, session history, user identifiers, traces, metrics, schedules, and audit events. Memory features can automatically store user facts, preferences, inputs, topics, agent IDs, team IDs, and update timestamps in connected databases; define consent, retention, correction, and deletion workflows. AgentOS and agent APIs can centralize sessions, memory, traces, schedules, RBAC, and audit logs in infrastructure the operator controls, so database credentials, backups, access controls, and exports need normal review. Model providers, vector stores, embedder providers, MCP servers, and tools may receive user data or internal context depending on the agent configuration. Agno's telemetry documentation says anonymous usage data is collected about agents, teams, workflows, and AgentOS configurations, and documents `AGNO_TELEMETRY=false` plus per-instance telemetry disabling. |
| Prerequisites |
| — none listed | — none listed |
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| Install | — | — | — | — |
| Config | — | — | — | — |
| Citations | ||||
| Claim | Unclaimed | Unclaimed | Unclaimed | Unclaimed |
Visual automation platform for integrations and AI workflows.
Source-backed guides for putting this to work.
Run AI dev tools, MCP servers, models, and memory on infrastructure you own.
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