Building GraphRAG TypeScript MCP tools
Create a Model Context Protocol server in TypeScript. Define type-safe Zod tools, resources, and prompts that connect AI agents to Neo4j graph data.
In this 2-hour course, you will learn
Building Full definition for GraphRAG (opens in a new tab)Retrieval-augmented generation whose context comes from a knowledge graph, so the model can follow the relationships between facts. TypeScript MCP tools teaches you how to create your own Model Context Protocol (MCP) server in TypeScript, exposing tools, resources, and prompts backed by a Neo4j graph database. In around two hours you will build a server that any MCP client can connect to and use to answer questions from a live graph.
Where Developing with Neo4j MCP Tools taught you to consume an existing server, this course teaches you to author one. Using the MCP TypeScript SDK, you will define type-safe tools with Zod schemas, manage the Neo4j driver behind them, and design the server features that let an AI agent work with your data reliably.
MCP Server Development with TypeScript
Build a fully functional Model Context Protocol server in TypeScript, defining tools, resources, and prompts that AI agents can invoke at runtime.
Neo4j Driver Lifecycle Management
Configure and manage the Neo4j JavaScript driver correctly, opening and closing sessions safely so your MCP server handles connections without leaking resources.
Context-Aware Tools with Zod Schemas
Write type-safe MCP tools using Zod to validate inputs, ensuring AI agents receive structured, predictable data from your Neo4j graph database.
Pagination for Large Datasets
Apply cursor-based and skip/limit pagination patterns so your MCP tools return manageable result sets without overwhelming the calling AI agent.
Text-to-Cypher Natural Language Queries
Implement a text-to-Cypher pipeline that translates natural language questions from an AI agent into executable Cypher queries against a Neo4j graph.
3 modules, 2 hours.
Who this course is for
This course is for TypeScript and Full definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties..js developers who want to give AI agents custom, graph-backed capabilities. Off-the-shelf MCP servers cover generic database access, but production applications need tools shaped around your domain: a query you have already tuned, a resource that publishes reference data, a prompt that encodes a workflow. It fits naturally into a TypeScript stack - Zod validates every tool argument before your code runs, a familiar Full definition for pattern (opens in a new tab)A graph structure written in Cypher, such as a node joined to another node by a relationship. if you have built typed APIs. You should be comfortable with TypeScript and the command line, and understand large language models, grounding, and the MCP host, client, and server architecture before you start; the prerequisite courses are listed beside this overview.
What you'll build and do
You will assemble a complete MCP server one feature at a time. After scaffolding a minimal server with the TypeScript SDK, you will wire in a Neo4j connection with a managed driver lifecycle, then build tools whose inputs are validated by Zod schemas, including a Full definition for GraphRAG (opens in a new tab)Retrieval-augmented generation whose context comes from a knowledge graph, so the model can follow the relationships between facts. tool that retrieves movie data to ground an agent's answers in facts from the graph. You will use the context object for logging and progress reporting, publish read-only data as resources, implement pagination so large result sets arrive in manageable pages, create prompts that hand reusable instructions to any connected client, and see how text-to-Cypher lets an agent translate natural language questions into graph queries.
Every feature is reinforced with a challenge: you implement it, connect a real MCP client, and confirm the agent can use what you built. You need Full definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties..js 20 or later and npm installed, plus a GitHub account with a Copilot plan enabled - the challenges use GitHub Copilot as the MCP client. GraphAcademy provides an online Neo4j instance loaded with a movie recommendations dataset.
Where to go next
If you also work in Python, Building GraphRAG Python MCP tools covers the equivalent journey with FastMCP and is quick to complete once you know the concepts in this course. To strengthen the data your tools serve, take Building Knowledge Graphs with LLMs, which shows you how to construct a Full definition for knowledge graph (opens in a new tab)A representation of real-world entities and their relationships, stored according to organizing principles, typically in a graph database. from unstructured text with the Go to glossary for large language model (opens in a new tab)A model trained on text to predict the next token, and so to generate language. Graph Builder. This course also prepares you for the Neo4j & Generative AI Certification, which validates your ability to build GenAI applications backed by Neo4j.