Which is more popular, Flock or n8n?

n8n has more GitHub stars (206,548 vs 1,114).

Which is more actively developed, Flock or n8n?

n8n had more commits in the last 90 days (3,694 vs 1).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

n8n is growing faster: +3,978 GitHub stars in the last 30 days vs +4 for Flock.
Pick Flock for: desktop multi-agent harness with visual workflows, built with Rust, Tauri, React, and langgraph-rust. Pick n8n for: fair-code workflow automation platform with native AI capabilities.

From GitHub data refreshed daily.

Flockopen-source

Desktop multi-agent harness with visual workflows, built with Rust, Tauri, React, and langgraph-rust

n8nfree

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

+Comprehensive low-code workflow builder with visual interface for creating complex AI applications without extensive programming
+Strong multi-agent orchestration capabilities with dedicated agent nodes and MCP protocol support for tool integration
+Modern architecture built on proven technologies (LangGraph, Langchain, FastAPI, NextJS) with active development and regular feature updates

+Hybrid approach combining visual workflow building with full JavaScript/Python coding capabilities when needed
+AI-native platform with LangChain integration for building sophisticated AI agent workflows using custom data and models
+Fair-code license ensures source code transparency with self-hosting options, providing data control and deployment flexibility

-Relatively new platform with limited documentation and community resources compared to established alternatives
-Complexity may be overwhelming for simple chatbot use cases that don't require advanced workflow orchestration
-Dependency on multiple underlying frameworks (LangGraph, Langchain) may introduce potential compatibility issues during updates

-Requires technical knowledge to fully leverage coding capabilities and advanced features
-Self-hosting demands infrastructure management and maintenance overhead
-Fair-code license restricts commercial usage at scale without enterprise licensing

•Building enterprise chatbots with complex multi-step workflows, human approval processes, and integration with existing business systems
•Implementing RAG systems that require orchestrated data retrieval, processing, and generation across multiple AI models and tools
•Creating multi-agent teams for collaborative task execution, where different specialized agents handle specific parts of complex workflows

•Building AI agent workflows that process customer data using LangChain and custom language models
•Automating complex business processes that require both API integrations and custom business logic
•Creating data synchronization pipelines between multiple SaaS tools while maintaining full control over sensitive data through self-hosting

Which is more popular, Flock or n8n?: n8n has more GitHub stars (206,548 vs 1,114).
Which is more actively developed, Flock or n8n?: n8n had more commits in the last 90 days (3,694 vs 1).
Should I use Flock or n8n?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.