[feature] Implement MCP prototype

[pinghe]

Implement MCP prototype

[michaelvlach]

Hi, I looked into the MCP and on the surface it looked like good addition to the agdb_server. I will need to look into it a bit more. Did you have any specific use case in mind?

[pinghe]

When constructing an LLM knowledge base, I aim to store the extracted knowledge graphs in agdb , a native graph database, for use in Retrieval-Augmented Generation (RAG) workflows. The integration of MCP (Model Context Protocol) with agdb enables seamless knowledge production (creation and structuring of graph data) and knowledge consumption (dynamic retrieval and application in LLM interactions).

Key Components Explained:

agdb :

• A self-contained, application-native graph database with no external dependencies, supporting constant-time lookups and memory-mapped persistence.
• Stores knowledge graphs as directed graphs with key-value properties on nodes/edges, ideal for representing entities and their relationships.

RAG Integration :

• Knowledge graphs in agdb can serve as structured external sources for RAG, enhancing LLM responses with contextual relationships (e.g., path queries or hierarchical reasoning).
• Combines vector-based retrieval (for semantic similarity) and graph traversal (for relational context) to improve accuracy.

MCP (Model Context Protocol) :

• A universal standard for connecting LLMs to data sources, enabling real-time updates and bidirectional interactions between agdb and AI tools.
• Facilitates secure, low-latency access to agdb’s graph data during LLM inference, reducing manual configuration overhead.

This workflow aligns with emerging practices where graph databases and protocols like MCP enhance the scalability and contextual relevance of LLM applications .