Made a massive curated list of 260+ AI agents & tools — heavy focus on open-source, self-hosted, and local-first options
Posted by Caramaschi@reddit | LocalLLaMA | View on Reddit | 7 comments
I put together what I think is the most comprehensive list of AI agents and frameworks available right now, with a big emphasis on open-source and self-hosted tools.
https://github.com/caramaschiHG/awesome-ai-agents-2026
Some highlights for this community:
**Local LLM Runners:** Ollama (162k stars), llama.cpp, vLLM, LM Studio, Jan, LocalAI, GPT4All, Llamafile
**Self-hosted agents:** OpenClaw (the 9k→188k stars phenomenon), 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 (lowest hallucination), Gemma 3, Phi-4
**Open-source video gen:** Wan 2.1 (self-hostable, no limits), HunyuanVideo, LTX Video
**OSS voice:** LiveKit Agents, Rasa, Pipecat, Vocode
**Browser infra:** Browser Use (what Manus uses under the hood), Skyvern, Agent S2
Plus vector DBs (Chroma, Qdrant, Milvus, Weaviate), RAG engines (RAGFlow, Pathway), safety tools (NeMo Guardrails, LLM Guard), and a lot more.
CC0 licensed. PRs welcome. What am I missing?
Dear_Temperature6370@reddit
Great list. One gap in the agent infrastructure section — payment rails for agents. If your agent needs real-time crypto data (price, whale activity, gas, TVL etc), AgentPay lets it pay per call in USDC via x402 instead of holding API keys. No subscription, budget-capped. Works as an MCP server too: https://github.com/romudille-bit/agentpay
niga_chan@reddit
this is actually a really solid list, nice work putting this together
one thing that feels slightly under-discussed is what happens when you actually try to run these agents at scale locally
we’ve been experimenting on that side and were able to push \~4.5k standby agents on a single node, and pretty quickly the bottleneck shifts from models/tools → orchestration + memory per agent
feels like there’s a missing layer around “agent infrastructure” that sits between all these frameworks and real-world usage
curious if you’ve come across anything focused more on that layer
APIS_AI@reddit
We built ContextGate: a dynamic HUD-style context header for agents.
Trusted local state up top, untrusted remote data kept separate, replaced each turn instead of bloating transcript history.
https://github.com/APIS-AI/contextgate
APIS_AI@reddit
A trusted DESKTOP header lets an agent keep live notes and runtime state without re-appending them through chat history.
That means more token budget stays available for the actual coding task.
My GPT-5.4 coding agent has been running for days and is still at 3% context.
EffectiveCeilingFan@reddit
In the future, when copy-pasting text from your chatbot, you need to make sure you're in the "markdown editor" in Reddit. That way it'll render the bold text instead of asterisks.
crypticFruition@reddit
Good list. Worth noting that OpenClaw pioneered the agent framework space, but the January OAuth revocation really changed what's viable for self-hosted setups. There are newer approaches now that sidestep those auth complications entirely.
fredconex@reddit
Maybe worth to be on list?
https://github.com/fredconex/Arandu