https://github.com/timothywarner-org/context-engineering

🧠 Stop building AI that forgets. Master MCP (Model Context Protocol) with production-ready semantic memory, hybrid RAG, and the WARNERCO Schematica teaching app. FastMCP + LangGraph + Vector/Graph stores. Your AI assistant's long-term memory starts here.
https://github.com/timothywarner-org/context-engineering

ai-agents ai-memory anthropic azure-ai-search chromadb claude context-engineering fastapi fastmcp hybrid-rag knowledge-graph langgraph llm mcp mcp-tools model-context-protocol python rag semantic-memory vector-database

Last synced: 2 months ago
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Host: GitHub
URL: https://github.com/timothywarner-org/context-engineering
Owner: timothywarner-org
License: mit
Created: 2025-07-08T17:23:01.000Z (10 months ago)
Default Branch: main
Last Pushed: 2026-01-27T22:31:13.000Z (3 months ago)
Last Synced: 2026-01-28T10:59:48.584Z (3 months ago)
Topics: ai-agents, ai-memory, anthropic, azure-ai-search, chromadb, claude, context-engineering, fastapi, fastmcp, hybrid-rag, knowledge-graph, langgraph, llm, mcp, mcp-tools, model-context-protocol, python, rag, semantic-memory, vector-database
Language: Python
Homepage: https://techtrainertim.com
Size: 71.2 MB
Stars: 12
Watchers: 1
Forks: 8
Open Issues: 1
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

          # Context Engineering with MCP: Build AI Systems That Actually Remember



Welcome to the training hub for mastering **Context Engineering with Model Context Protocol (MCP)**. This course teaches you to implement production-ready semantic memory systems for AI assistants using Python, FastAPI, FastMCP, and LangGraph.

---

## Quick Start

### Prerequisites

- Python 3.11+ (3.12+ recommended for WARNERCO Schematica)

- Node.js 20+ (for Lab 01 and MCP Inspector)

- [uv](https://docs.astral.sh/uv/) package manager (recommended for Python)

- Claude Desktop or Claude Code

### Option 1: Hello MCP Lab (Beginner Entry Point)

```bash

git clone https://github.com/timothywarner-org/context-engineering.git

cd context-engineering/labs/lab-01-hello-mcp/starter

npm install && npm start

# Test with MCP Inspector (in another terminal)

npx @modelcontextprotocol/inspector node src/index.js

```

### Option 2: WARNERCO Schematica (Flagship Teaching App)

```bash

cd src/warnerco/backend

uv sync

uv run uvicorn app.main:app --reload    # HTTP server at http://localhost:8000

uv run warnerco-mcp                      # MCP stdio server for Claude Desktop

```

---

## Course Structure (4 x 50 Minutes)

| Segment | Topic                  | Focus                                                           |

| ------- | ---------------------- | --------------------------------------------------------------- |

| **1**   | All About Context      | Token economics, context loss types, why RAG isn't enough       |

| **2**   | All About MCP          | FastMCP, FastAPI, tools, resources, prompts, elicitations       |

| **3**   | Semantic Memory Stores | JSON, ChromaDB, Azure AI Search, Graph Memory, Scratchpad       |

| **4**   | MCP in Production      | Claude Desktop, Claude Code, VS Code, GitHub Copilot, LangGraph |

---

## WARNERCO Schematica Architecture

The flagship teaching application demonstrates production MCP patterns with a 7-node hybrid RAG pipeline:

```

+---------------------------------------------------------------+

|                     FastAPI + FastMCP                         |

+---------------------------------------------------------------+

|  LangGraph Flow (7-node Hybrid RAG)                           |

|  parse_intent -> query_graph -> inject_scratchpad -> retrieve |

|  -> compress -> reason -> respond                             |

+---------------------------------------------------------------+

|  Hybrid Memory Layer                                          |

|  +-------------------+  +-------------------+  +-------------+ |

|  | Vector Store      |  | Graph Store       |  | Scratchpad  | |

|  | JSON -> Chroma -> |  | SQLite + NetworkX |  | In-memory   | |

|  | Azure AI Search   |  | (Knowledge Graph) |  | (Session)   | |

|  +-------------------+  +-------------------+  +-------------+ |

+---------------------------------------------------------------+

```

### Memory Store Comparison

| Feature              | JSON         | ChromaDB      | Azure AI Search    | Graph       | Scratchpad     |

| -------------------- | ------------ | ------------- | ------------------ | ----------- | -------------- |

| Semantic Search      | No           | Yes           | Yes                | No          | No             |

| Relationship Queries | No           | No            | No                 | Yes         | No             |

| Session Memory       | No           | No            | No                 | No          | Yes            |

| Best For             | Prototyping  | Local dev     | Production         | Connections | Working memory |

---

## Repository Structure

```

context-engineering/

├── src/warnerco/backend/      # WARNERCO Schematica (FastAPI + FastMCP + LangGraph)

├── labs/lab-01-hello-mcp/     # Hands-on beginner lab

├── docs/                      # Student materials, tutorials, diagrams

├── instructor/                # Instructor-only materials

├── config/                    # Sample MCP client configurations

├── .vscode/                   # VS Code workspace configuration

├── .claude/                   # Claude Code agents and skills

└── CLAUDE.md                  # Development instructions (SOURCE OF TRUTH)

```

**For development details, see [CLAUDE.md](CLAUDE.md)** - the source of truth for:

- Complete MCP tool reference

- API endpoint documentation

- Environment variable configuration

- LangGraph pipeline details

- Graph and Scratchpad Memory features

---

## MCP Client Configuration

### Claude Desktop

**Windows**: `%APPDATA%\Claude\claude_desktop_config.json`

**Mac**: `~/Library/Application Support/Claude/claude_desktop_config.json`

```json

{

  "mcpServers": {

    "warnerco": {

      "command": "uv",

      "args": ["run", "warnerco-mcp"],

      "cwd": "C:/github/context-engineering/src/warnerco/backend"

    }

  }

}

```

### VS Code

See `.vscode/mcp.json` in the repository for local and Azure APIM configurations.

---

## Testing with MCP Inspector

```bash

npx @modelcontextprotocol/inspector uv run warnerco-mcp

# Opens http://localhost:5173

```

---

## Resources

- **[MCP Specification](https://spec.modelcontextprotocol.io/)** - Official protocol documentation

- **[FastMCP Documentation](https://github.com/jlowin/fastmcp)** - Python MCP framework

- **[CLAUDE.md](CLAUDE.md)** - Development instructions for this repository

---

## Your Instructor

### Tim Warner

**Microsoft MVP** - Azure AI and Cloud/Datacenter Management

**Microsoft Certified Trainer** (25+ years)

- Website: [techtrainertim.com](https://techtrainertim.com)

- GitHub: [@timothywarner](https://github.com/timothywarner)

- LinkedIn: [linkedin.com/in/timothywarner](https://www.linkedin.com/in/timothywarner/)

---

## License

MIT License - 2026 Timothy Warner

---

**Now go build AI systems that actually remember!**

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