head to head · open source

Agent-Reach vs langtrace

Agent-Reach has 83,525 GitHub stars, 7,317 forks, 137 open issues and last shipped 5 days ago. langtrace has 1,232 stars, 127 forks, 2 open issues and last shipped 10 months ago. Agent-Reach leads on adoption by 6,680% (83,525 vs 1,232 stars). Agent-Reach is written in Python under MIT; langtrace is written in TypeScript under AGPL-3.0. Agent-Reach has attracted 9% as many forks as stars, langtrace 10%. Agent-Reach was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Agent-Reach ★ 84K langtrace ★ 1.2K category AI & Machine Learning

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Side by side

Agent-Reach langtrace
GitHub stars ★ 84K ★ 1.2K
License MIT AGPL-3.0
Written in Python TypeScript
Last push 2026-09-15 2025-11-17
Forks ⑂ 7.3K ⑂ 127
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agent-Reach if

  • You weight community size — 84K stars and counting
  • You want the MIT license terms
  • Your stack matches Python
  • You value the larger contributor base for long-term maintenance

full Agent-Reach profile →

pick langtrace if

  • You want the langtrace feature set and don't need the biggest community
  • You prefer the AGPL-3.0 license terms
  • Your stack matches TypeScript
  • You evaluated both and langtrace fits your workflow better

full langtrace profile →

About Agent-Reach

Agent Reach is an open source Python command line tool that gives AI agents the ability to read and search the wider internet — Twitter/X, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu among others — for developers and agent builders who want that reach without paying for platform APIs.

read the full Agent-Reach overview →

About langtrace

Langtrace is an open source, OpenTelemetry based end to end observability tool for LLM applications that captures and analyzes real time traces, evaluations and metrics across LLM APIs, vector databases and LLM frameworks, and it is aimed at developers and LLMOps teams who need to see what their LLM backed applications are actually doing in production.

read the full langtrace overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

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openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all

More AI Development Platforms projects

Compare either of these against the rest of the AI Development Platforms field.

Agent-Reach vs Dify Agent-Reach vs langchain Agent-Reach vs ponytail Agent-Reach vs generative-ai-for-beginners Agent-Reach vs graphify Agent-Reach vs claude-mem Agent-Reach vs ragflow Agent-Reach vs PaddleOCR Agent-Reach vs headroom Agent-Reach vs Mem0 Agent-Reach vs daily_stock_analysis Agent-Reach vs LiteLLM

Frequently asked questions

Is Agent-Reach or langtrace more popular?

Agent-Reach has 83,525 GitHub stars and langtrace has 1,232. Agent-Reach has the larger community by that measure.

Are Agent-Reach and langtrace free?

Both are open source. Agent-Reach is licensed under MIT and langtrace under AGPL-3.0. Neither carries a licence fee.

What is the difference between Agent-Reach and langtrace?

Agent-Reach is written in Python and langtrace in TypeScript. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Agent-Reach or langtrace?

Choose Agent-Reach if you want the larger community (83,525 stars) or its MIT licence terms. Choose langtrace if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.