LLM Agents & Ecosystem Handbook A unified handbook for building, deploying and understanding LLM agents and the wider ecosystem A polished, curated collection of Large Language Model (LLM) agents, tutorials and ecosystem insights. This handbook highlights projects that push the boundaries of generative AI, multi-agent collaboration, retrieval-augmented generation (RAG), voice and game agents, and more. It goes beyond simple link aggregation, aiming to be a one-stop reference for building, deploying, and understanding LLM applications across the entire stack.
| Stars | 541 |
| Forks | 85 |
| Language | Python |
| Category | MCP 服务器 |
| License | MIT |
| Quality Score | 68.3382629088946/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-30 |
| Created | 2025-09-08 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
These tools work well together with LLM-Agents-Ecosystem-Handbook for enhanced workflows:
Explore other popular mcp 服务器 tools:
LLM-Agents-Ecosystem-Handbook is One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.. It is categorized as a MCP 服务器 with 541 GitHub stars.
LLM-Agents-Ecosystem-Handbook is primarily written in Python. It covers topics such as ai, ai-agent, ai-agents.
You can find installation instructions and usage details in the LLM-Agents-Ecosystem-Handbook GitHub repository at github.com/oxbshw/LLM-Agents-Ecosystem-Handbook. The project has 541 stars and 85 forks, indicating an active community.
LLM-Agents-Ecosystem-Handbook is released under the MIT license, making it free to use and modify according to the license terms.