Technical guides on agentic AI, MCP search, retrieval quality, and systems that retrieve reliably.
Claude Code is strongest when it has the right context before it edits. Here is how to connect Ninelayer through MCP when generic search creates noisy context, stale docs, and expensive retry loops.
AI agents like Claude Code, Cursor, and Codex are only as reliable as the context they can retrieve. Search is becoming the infrastructure layer that keeps agents grounded, current, and useful.
Your AI agent may be burning thousands of tokens on boilerplate before it starts thinking. Here is the math behind retrieval waste, and why clean, agent-native search matters.
