Agentic Graph RAG Pipeline with Multi-Hop Reasoning, Self-Correction & Knowledge Graphs in LangGraph

Engineer a real-time voice agent that streams speech-to-text, orchestrates an LLM with tool calling, and synthesizes speech so the conversational loop stays under 300ms perceived latency, with confidence thresholds and human escalation as safety nets.

Give agents durable memory. Combine mem0 as the universal memory layer with LangGraph orchestration and a vector store to persist user, session, and agent-level context across sessions, channels, and devices, with adaptive updates that avoid memory bloat.

Build a Weaviate Vector Database MCP server for Claude Desktop and Cursor: BM25+dense hybrid search, vectorization, typed cross-references for graph RAG, and an OAuth 2.0 secured streamable-HTTP transport.

Enforce the OWASP Top 10 for LLM Applications 2026 from an MCP server: LLM01 prompt-injection blocking, Presidio PII redaction, Gitleaks secrets detection, and system-prompt-leak defense for Claude Desktop and Cursor.

OWASP's Top 10 for LLM Applications 2026 (released Aug 2026) adds vector and embedding weaknesses, maps every risk to NIST AI RMF and MITRE ATLAS, and turns agentic AI security into a repeatable audit. Here is the full checklist.