newsletterJune 15, 2026·Towards Data Science

The Protocol That Cleaned Up Our Agent Architecture

A detailed look at MCP that turned my scattered tool definitions into a stable, discoverable server The post The Protocol That Cleaned Up Our Agent Architecture appeared first on Towards Data Science.

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•A detailed look at MCP that turned my scattered tool definitions into a stable, discoverable server The post The Protocol That Cleaned Up Our Agent Architecture appeared first on Towards Data Science.
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Discussion

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The Protocol That Cleaned Up Our Agent Architecture

Key Takeaways

Related Articles

How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs

Cut an Enterprise RAG Pipeline’s Latency and Cost by Calling the LLM Less, Not by Buying a Faster Model

How to Orchestrate a Fleet of OpenClaw Bots

LangChain vs LangGraph: 4 Key Differences and When to Use Each

Discussion

The Protocol That Cleaned Up Our Agent Architecture

Key Takeaways

Related Articles

How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs

Cut an Enterprise RAG Pipeline’s Latency and Cost by Calling the LLM Less, Not by Buying a Faster Model

How to Orchestrate a Fleet of OpenClaw Bots

LangChain vs LangGraph: 4 Key Differences and When to Use Each

Discussion

Related Articles

Towards Data Science
How to Utilize OKF Efficiently to Enable Knowledge Exchange Among LLMs
Google's Open Knowledge Format (OKF) is a Markdown+YAML skeleton for sharing knowledge between humans and AI agents. This post reuses that skeleton for a very specific job — an agent-to-agent hand-off of pre-tokenized integer arrays between three Qwen2.5-Coder models (7B, 3B, 1.5B) — and shows the 2

Towards Data Science
Cut an Enterprise RAG Pipeline’s Latency and Cost by Calling the LLM Less, Not by Buying a Faster Model
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