Streaming WebFlux API for MCP server

[kornelrabczak]

Current MCP server uses a traditional request-response model where the entire payload is assembled in memory before being sent to the client. For large knowledge graphs, this creates problems:

• High memory usage, read_graph materializes ALL entities and relations into a single response
• Latency, clients must wait for the entire graph to be serialized before receiving any data
• Large graph reads (read_graph) may OOM
• Poor LLM experience, LLMs could start processing partial results immediately instead of waiting

Proposal

Introduce a streaming API using Spring WebFlux reactive types (Flux) to stream graph data directly to LLM clients as it is read from LadybugDB, instead of buffering the entire result set.