Wiring MCP Servers Into Claude Cowork Safely
Connect MCP servers to Claude Cowork safely: scoped auth, tight tool schemas, structured error handling, and idempotency keys that prevent duplicate actions.
Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Connect MCP servers to Claude Cowork safely: scoped auth, tight tool schemas, structured error handling, and idempotency keys that prevent duplicate actions.
Code-level patterns for Claude Cowork: single-responsibility skills, typed tool contracts, layered context, intent-named idempotent tools, and clean handoffs.
Step-by-step Claude Cowork deployment: build a read-only MCP connector, write and test a skill, bundle a role plugin, and pilot safely with one team.
End-to-end look at Claude Cowork's internals — plugins, skills, MCP connectors, and sub-agents — and how to govern each layer in an enterprise rollout.
An agentic-AI perspective on Computer Use 2.0, covering orchestration patterns, tool use, and how browser agents fits production agent stacks.
A practical engineering deep dive into Claude Haiku 4.5 classification, covering architecture, tradeoffs, and what production teams need to know about high throughput AI.
A practical engineering deep dive into Claude Opus 4.7 research, covering architecture, tradeoffs, and what production teams need to know about literature review.
LangGraph's streaming primitives let you push tokens, node events, and tool calls to the UI in real time. The four streaming modes explained with examples.
LlamaIndex's event-driven Workflows are the cleanest async agent primitive of 2026. A walkthrough with real RAG-with-tools examples and the gotchas to avoid.