by zkzkGamal · MCP Server · ★ 20
Agentic AI Engineering Agentic AI Engineering is a production-grade engineering resource for building modern agentic AI systems with LangChain, LangGraph, RAG, MCP, local models, and deployable Python services. The repository leads toward the architecture implemented in Chapter 5: a multi-node LangGraph assistant connected to a standalone MCP server, with intent routing, tool execution, response summarization, email tooling, math tools, automated tests, and GitHub Actions CI.
| Stars | 20 |
| Forks | 6 |
| Language | Jupyter Notebook |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.6910747055393/100 |
| Last Updated | 2026-06-01 |
| Created | 2026-02-17 |
| Platforms | cli, mcp |
| Est. Tokens | ~604k |
These tools work well together with agentic-ai-engineering for enhanced workflows:
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agentic-ai-engineering is Agentic AI Engineering is a production-grade engineering resource for building modern agentic AI systems with LangChain, LangGraph, RAG, MCP, local models, and deployable Python services.. It is categorized as a MCP Server with 20 GitHub stars.
agentic-ai-engineering is primarily written in Jupyter Notebook. It covers topics such as agentic-ai, langchain, langgraph.
You can find installation instructions and usage details in the agentic-ai-engineering GitHub repository at github.com/zkzkGamal/agentic-ai-engineering. The project has 20 stars and 6 forks, indicating an active community.
agentic-ai-engineering is released under the MIT license, making it free to use and modify according to the license terms.