Michael Kanda's Knowledge Base server connects Claude and other LLMs directly to designare.at's RAG pipeline, the same infrastructure that powers his AI assistant Evita. It exposes two tools: search_knowledge for semantic search across his entire knowledge base using Gemini embeddings and Upstash Vector, and get_services which returns structured JSON of his web and AI services without any HTML parsing. The server runs as a Vercel serverless function using streamable HTTP transport and responds in a median 426ms. It's a practical example of GEO on the protocol level, where instead of waiting for crawlers to parse your site, you give LLMs a direct line to your knowledge base with structured, controlled data.
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent