deer-flow logo
deer-flow
★ 84.3k
vs
commonly logo
commonly
★ 1.4k

deer-flow vs commonly

deer-flow: DeerFlow is a community-driven framework designed for deep research, integrating language models with specialized tools for tasks like web search, crawling, and Python code execution. It offers a modular multi-agent system architecture for automated research, supporting various search engines, crawling tools, and private knowledge bases.; commonly: Commonly is an open-source workspace where people and agents from different runtimes work in shared pods with threaded chat, persistent memory and a task board. Agents join as named seats with their own identity and memory, and can connect through a local daemon, the CLI or an MCP package.

01

TL;DR

deer-flow logo
deer-flowMulti-Agent · ★ 84.3k
When to choose:
  • You want a batteries-included LangGraph agent runtime with a file system, isolated bash/Docker sandbox, persistent memory, and sub-agent delegation.
  • You want to trigger long-running tasks from Feishu, WeCom, DingTalk, WeChat, Slack, or Telegram without exposing a public IP.
When to skip:
  • Your machine or VPS has only 2 vCPU / 4 GB RAM; DeerFlow recommends 8 vCPU / 16 GB RAM for shared servers.
  • You only want a lightweight script that writes cited web research reports without running local sandboxes; GPT Researcher is much lighter.
commonly logo
commonlyMulti-Agent · ★ 1.4k

Running a small team where several coding agents and humans share one task board

02

Side-by-Side Comparison

Field
deer-flow logodeer-flow
commonly logocommonly
Category
Multi-Agent
Multi-Agent
Stars
★ 84.3k
★ 1.4k
License
MIT
Apache-2.0
Install Command
uv sync
git clone https://github.com/Team-Commonly/commonly.git && cd commonly && ./install.sh
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
LLM, Multi-Agent, Research Automation
multi-agent, collaboration, self-hosted
03

Features

deer-flow logodeer-flow
01Multi-model LLM integration via LiteLLM with OpenAI-compatible API
02Comprehensive web search and crawling using diverse engines like InfoQuest and Tavily
03RAG integration with multiple vector databases including Qdrant and RAGFlow
04Human-in-the-loop collaboration with intelligent clarification and interactive plan modification
05Automated content creation for podcasts and presentations with AI-powered script generation
commonly logocommonly
01Pods with human and agent members, threaded chat, pod memory and a Kanban board synced with GitHub Issues
02Bring your own runtime: Claude Code, Codex or custom HTTP agents via daemon, CLI or the @commonlyai/mcp package
03Connectors and scoped grants that give agents a capability without sharing the underlying secret
04Heartbeat scheduler so agents can claim tasks and work on a fixed interval
05Local self-hosting with one Docker Compose install script
04

Use Cases

deer-flow logodeer-flow
↳Conducting deep research and generating comprehensive reports with multimedia content
↳Automated creation of podcasts, articles, and presentations from research findings
↳Intelligent information retrieval and analysis for complex queries and trending topics
commonly logocommonly
↳Running a small team where several coding agents and humans share one task board
↳Giving existing agents in Claude Code or Cursor a shared memory and chat channel
↳Routing work from Slack-like channels to agents with limited, auditable access
05

Best For

deer-flow logodeer-flow
Most PopularEssentialTrending
commonly logocommonly
EssentialTrending
FAQ

FAQ

What is the difference between deer-flow and commonly?
Both deer-flow and commonly are in the Multi-Agent category. deer-flow has 84.3k stars, while commonly has 1.4k stars.
Which is better, deer-flow or commonly?
The best choice depends on your use case. Choose deer-flow if Conducting deep research and generating comprehensive reports with multimedia content, and commonly if Running a small team where several coding agents and humans share one task board.
Is deer-flow free or open source?
Yes, deer-flow is open source on GitHub (MIT).
Is commonly free or open source?
Yes, commonly is open source on GitHub (Apache-2.0).
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