I built an MCP server for a knowledge graph. It doesn't call any LLM.

1. 1Build a knowledge graph using a graph database like Neo4j or Amazon Neptune
2. 2Configure a data processing pipeline to extract entities from text data without using LLMs
3. 3Implement a custom entity extraction algorithm using techniques like named entity recognition or rule-based approaches
4. 4Test and evaluate the performance of the entity extraction algorithm
5. 5Integrate the MCP server with the knowledge graph to enable querying and reasoning

Developers and data scientists working on knowledge graph projects can benefit from this approach, as it provides a unique perspective on entity extraction and data processing

💡 You don't need LLMs to build an effective MCP server for knowledge graphs, and alternative approaches can be just as effective

Build an MCP server for knowledge graphs without LLMs! Discover alternative entity extraction approaches #knowledgegraph #entityextraction