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agentic-engineering-handbook MCP Server

Name: keyuchen21/agentic-engineering-handbook
Rating: 3.3 (1 reviews)
Author: keyuchen21

keyuchen21/agentic-engineering-handbook

Score: 56.5 Rank #8166 MCP Server

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The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.

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Overview

keyuchen21/agentic-engineering-handbook is a Python tool licensed under MIT. The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap. Topics: agentic-engineering, agents, ai-agents, anthropic, claude-code, llm, mcp, openai.

Ranked #8166 out of 24846 indexed tools.

Ecosystem

Python MIT

agentic-engineeringagentsai-agentsanthropicclaude-codellmmcpopenai

Score Breakdown

Stars 15% 549

549 stars → growing community

Freshness 25% 1mo ago

Last commit 1mo ago → moderate activity

Issue Health 25% 0%

0/1 issues closed → many open issues

Contributors 10% 1

1 contributor → solo project

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A

PyPI Downloads N/A

Forks 69

Description Good

License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

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Description low impact

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Freshness high impact

Last commit was 31 days ago — a recent commit would boost your freshness score

Issue Health high impact

You have 1 open vs 0 closed issues — triaging stale issues improves health

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Details

Stars: 549
Forks: 69
Open Issues: 1
Closed Issues: 0
Contributors: 1
Dependents: —
Language: Python
License: MIT
Last Commit: 1mo ago

Matched Queries

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From the README

# Agentic Engineering Handbook

> The definitive OpenAI, Anthropic, Google, MCP, Harness, Evals, and Production Agent Systems learning roadmap.

If this repository helps you, consider giving it a ⭐

---

## Why This Repository?

The AI industry has entered the **Agentic Era**. Building production-grade AI systems now requires mastering agents, tool use, MCP, memory, long-running workflows, coding agents, agent harnesses, evals, and safety — but the knowledge is scattered across OpenAI blogs, Anthropic engineering posts, SDK docs, cookbooks, and research papers.

This repository consolidates **206 curated resources** into one structured learning roadmap.

**The goal: Become a world-class Agentic Engineer.**

---

## How To Use This Handbook

Pick the path that matches your starting point:

- **New to agents:** follow the [Learning Roadmap](#learning-roadmap) through the core Phases 0–6, then continue to [Phase 7](#phase-7--advanced-coursework-agent-training--search) for advanced coursew

Read full README on GitHub →