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7 articles tagged #MCP.
P.01LangChain 1.4's new langchain.mcp namespace turns any MCP server into an agent tool with one adapter. Here's how MCPAdapter, caching, and elicitation work.
P.02The OpenAI Agents API runs the Codex harness for you: durable sessions, sandboxes and MCP tools. How to integrate it in Python, and when to pick something else.
P.03WebMCP is a W3C proposal letting a page register JavaScript functions as tools an agent calls in-browser, no server MCP. How it works, and where it breaks.
P.04Only 8.5% of public MCP servers use OAuth, and a honeypot got hit within 48 hours. The checklist for auth, tool scoping, and input handling before you ship.
P.05EditorPickContext engineering means choosing what enters an LLM's context window: instructions, retrieved docs, tool output, memory and history. Eight techniques.
P.06EditorPickUse multiple agents when one agent has too many tools or too much context. The core patterns, MCP as the tool layer, and real code for three agent SDKs.
P.07MCP servers connect AI models to external tools and data. This guide covers building, deploying, and debugging them in production, with real code.