Curated list of 260+ AI agents and tools with open-source and self-hosted focus
Massive curated collection of AI development tools
A developer has compiled what they describe as the most comprehensive list of AI agents and frameworks currently available, with strong emphasis on open-source and self-hosted options. The repository is CC0 licensed and accepts pull requests for additions.
Key categories and tools
The list organizes tools into several functional categories:
- Local LLM Runners: Ollama (162k stars), llama.cpp, vLLM, LM Studio, Jan, LocalAI, GPT4All, Llamafile
- Self-hosted agents: OpenClaw (noted as growing from 9k to 188k stars), Open WebUI, LibreChat, LobeChat, Anything LLM, DB-GPT
- Open-source frameworks: Smolagents (HuggingFace), DeerFlow (ByteDance, #1 trending), LangGraph, CrewAI, AutoGen, Mastra
- Open-weight models for agents: Llama 4, Qwen 3 (MCP-native), DeepSeek V3/R1, GLM-4 (described as having lowest hallucination), Gemma 3, Phi-4
- Open-source video generation: Wan 2.1 (self-hostable, no limits), HunyuanVideo, LTX Video
- Open-source voice tools: LiveKit Agents, Rasa, Pipecat, Vocode
- Browser infrastructure: Browser Use (used by Manus under the hood), Skyvern, Agent S2
The repository also includes vector databases (Chroma, Qdrant, Milvus, Weaviate), RAG engines (RAGFlow, Pathway), and safety tools (NeMo Guardrails, LLM Guard).
📖 Read the full source: r/LocalLLaMA
👀 See Also
Constrails: Early-Alpha External Governance Layer for AI Agents
Constrails is an external runtime governance layer for AI agents that places a control layer between agents and their tools, implementing capability checks, risk scoring, policy evaluation, and audit logging. The early-alpha project aims to address safety concerns by moving controls outside the agent itself.
Customizing Claude AI for Improved Feedback
Adjust Claude AI's settings to avoid excessive agreement and push for more critical thinking and practical feedback.
Two Patterns for Preventing AI Agent Memory Rot: AutoDream and Skeptical Retrieval
OpenClaw introduces two MIT-licensed patterns to address file-based AI memory rot: AutoDream for nightly memory consolidation and Skeptical Retrieval for decay-weighted memory scoring. Both work together in a self-improving loop to keep agent context current.
oMLX introduces SSD KV caching for Apple Silicon, reducing OpenClaw response times from 30-90 seconds to 5 seconds
oMLX is a new backend that persists KV cache blocks to SSD in safetensors format, preventing cache invalidation when context shifts. This reduces OpenClaw response times from 30-90 seconds down to 5 seconds on subsequent turns.