innovation-lab-examples

Why we included this project

Developers getting into agentic AI often find themselves juggling frameworks, protocols, and model SDKs without a clear picture of how the pieces fit together. This collection shortens that learning curve with more than 80 runnable Python examples covering uAgents, ASI:One, the A2A protocol, MCP, LangChain, CrewAI, and model providers like Gemini, Claude, and OpenAI, so you can compare how different stacks handle similar tasks. The examples are written as working references rather than toy snippets, which makes them useful when you need to prototype a specific pattern quickly, such as wiring an agent to an external API or connecting several MCP servers. Docker support means you can run them without fighting your local setup, and the organization around real integrations makes the repo a solid study path for newcomers who want to see idiomatic implementations. Just keep in mind it is a pattern library, not a runtime you deploy; treat it as a source of starting templates for your own systems.