GraphAcademy

Graphify is a command-line tool and agent skill that turns a codebase and related project materials—including documentation, SQL schemas, configuration files, PDFs, images, and videos—into a locally queryable knowledge graph. It uses deterministic, local tree-sitter AST parsing for code, while non-code materials can receive a semantic pass from the configured AI assistant or API key; it does not use embeddings or a vector store. Graphify labels graph edges as EXTRACTED when they are explicit in the source or INFERRED when resolved by the tool, and can generate a clickable graph.html visualization, a GRAPH_REPORT.md summary, and a graph.json representation for later queries. The CLI is installed as the graphifyy package, registered with `graphify install`, and invoked through `/graphify` in supported AI coding assistants such as Claude Code, Cursor, Codex, Gemini CLI, and GitHub Copilot. The project is developed by Graphify Labs and provides free, fully local code mapping; its homepage describes a separate Graphify platform available through early access.

AI Engineering Lab is a free, self-paced 24-week AI engineering course developed by Zorost Intelligence AI Lab. It takes learners from Python and machine learning through deep learning, LLM internals, prompt and context engineering, retrieval-augmented generation with vector search, quantization, LoRA and DPO fine-tuning, evaluation harnesses, coding-agent harnesses, AI agents, MCP, and cloud and Databricks platforms including Azure AI Foundry, Google Vertex AI, AWS Bedrock, and Databricks. The curriculum uses one continuous fictional freight-company case study. Each week pairs a concept with a runnable Python, SQL, or PySpark artifact; from Week 3 onward, the work includes a metric and an error note. The repository contains 43 runnable notebooks, publishes the full curriculum online, requires no signup or paid API key, and states that the first eight weeks require no GPU. It is MIT licensed.

Code-Graph-RAG is an open-source retrieval-augmented generation system for querying, understanding, and editing multilingual codebases. Its Tree-sitter-based parser extracts functions, classes, methods, modules, and relationships, then stores them in Memgraph under a unified graph schema. An interactive CLI converts natural-language questions into Cypher queries, retrieves source code by name or intent, and supports AI-assisted editing and optimization. It provides AST-based surgical patches with diff previews, structural search and rewriting through ast-grep, dead-code discovery by traversing call and reference edges, and runtime-call overlays from test traces or production eBPF profiles. The project also supports MCP integration and publishes the `cgr` command-line tool to PyPI.

CodeGraph is a local code-intelligence tool for AI coding agents, distributed as a CLI, MCP server, and embeddable npm library by Colby McHenry. It parses source code into a SQLite knowledge graph of symbols, files, calls, imports, inheritance, dependencies, framework routes, and cross-language bridges, then resolves references and provides full-text search, source context, call paths, callers, callees, impact analysis, and affected-test discovery. Its primary MCP operation, codegraph_explore, returns relevant verbatim source together with relationships and blast-radius information so agents can query structure without file-by-file exploration. A native Rust parsing kernel supports more than 20 languages, with a portable fallback for unsupported platforms or files that fail native parsing. A native file watcher incrementally updates the local graph after changes, while connect-time reconciliation catches edits made between agent sessions. The tool installs and configures MCP integrations for agents including Claude Code, Cursor, Codex CLI, OpenCode, Gemini CLI, and GitHub Copilot; projects are initialized with codegraph init and stored locally under .codegraph. The repository states that the software is MIT-licensed and that telemetry can be disabled.

Neo4j Aura is Neo4j’s fully managed cloud graph database offering for storing and querying connected data at scale. In the described agent setup, it provides the cloud Neo4j instance used to inspect and store a connected memory graph; Neo4j also describes Aura as part of its Graph Intelligence Platform, alongside managed graph analytics and agent-building capabilities.