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Create Context Graph

Create Context Graph is an interactive CLI scaffolding tool that generates complete, domain-specific context graph applications. Think of it as create-next-app, but for AI agents backed by graph memory.

Given a domain (like healthcare, financial services, or wildlife management) and an agent framework, it generates a full-stack application: a FastAPI backend with a configured AI agent, a Next.js + Chakra UI frontend with NVL graph visualization, a Neo4j schema with synthetic data, and domain-specific tools that let the agent query and reason over your knowledge graph.

Key Features​

  • 22 built-in domains -- healthcare, financial services, real estate, manufacturing, scientific research, software engineering, and more. Each domain ships with a complete ontology, agent tools, demo scenarios, and fixture data.
  • 8 agent frameworks -- PydanticAI, Claude Agent SDK, OpenAI Agents SDK, LangGraph, CrewAI, Strands, Google ADK, and Anthropic Tools. Pick the one you know, or try something new.
  • Multi-turn conversations -- every generated agent uses neo4j-agent-memory for conversation persistence. Session history is stored in Neo4j and retrieved on each turn, so follow-up questions work naturally.
  • Graph-native AI agents -- every generated agent comes with Cypher-powered tools for querying entities, relationships, and decision traces in Neo4j. Tool calls stream in real-time with live progress indicators.
  • Streaming chat -- responses stream token-by-token via Server-Sent Events. Tool calls appear as a live timeline with spinner indicators as each executes. The graph visualization updates incrementally after each tool completes, not just at the end.
  • Interactive graph visualization -- the frontend includes an NVL-powered graph explorer with entity detail panel (click any node to see all properties and connections), a document browser with template filtering, and a decision trace viewer.
  • Rich demo data -- each domain ships with LLM-generated fixture data: 80-90 entities with realistic names, 25+ professional documents (discharge summaries, trade confirmations, lab reports), and 3-5 multi-step decision traces. All loaded into Neo4j via make seed and browsable in the frontend.
  • Flexible Neo4j setup -- connect to Neo4j Aura (free cloud tier with .env import), run locally with @johnymontana/neo4j-local (no Docker needed), use Docker Compose, or connect to any existing instance.
  • SaaS data import -- connect Gmail, Slack, Jira, GitHub, Notion, and Salesforce to populate your graph with real data.
  • Custom domains -- describe your domain and let the tool generate a complete ontology, or write your own YAML definition from scratch.

Quick Install​

No installation required. Run directly with uvx (Python) or npx (Node.js):

# Python (recommended)
uvx create-context-graph

# Node.js
npx create-context-graph

Quick Start (Non-Interactive)​

Skip the wizard entirely by passing flags:

uvx create-context-graph my-app \
  --domain healthcare \
  --framework pydanticai \
  --demo-data

This creates a my-app/ directory with a complete healthcare context graph application using PydanticAI as the agent framework, pre-loaded with demo data.

See All Available Domains​

uvx create-context-graph --list-domains

What's Next​