Building GraphRAG Python MCP tools
This course follows on from the Developing with Neo4j MCP Tools course, which introduces the Model Context Protocol and key concepts like Servers, Clients and Tools.
In this course, you will build on that knowledge to create your own MCP server using the MCP Python SDK and create server features that can be consumed by any MCP client.
Prerequisites
This course assumes that you have are familiar with the basics of Generative AI and Large Language Models. If you are not, we recommend that you take the GenAI Fundamentals and Developing with Neo4j MCP Tools courses first.
We also assume a basic understanding of Python and command line tools. We assume that you have Python installed along with the uv package manager.
If you are not familiar with uv, you should also review the uv documentation.
The course features hands-on challenges using GitHub CoPilot, you will need to enable either the free or Pro version.
Duration
2 hours
What you will learn
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How to build MCP servers with the MCP Python SDK and FastMCP
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How to connect your server to Neo4j using lifespan management
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How to create tools with context, logging, and structured outputs
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How to expose resources and prompts through your server
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How to implement pagination for large Neo4j datasets
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How to integrate MCP tools into development workflows
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Advanced features: Sampling and Completions (optional)
This course includes
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14 lessons across 3 modules (including setup)
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7 hands-on challenges with Neo4j
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Quiz questions to check your understanding
Get Support
If you find yourself stuck at any stage then our friendly community will be happy to help. You can reach out for help on the Neo4j Community Site, or head over to the Neo4j Discord server for real-time discussions.
Feedback
If you have any comments or feedback on this course you can email us on graphacademy@neo4j.com.