Tool Calls With Agentic Code Generation Using 'Monty'

Inspired by Anthropic’s recent article on using code execution to improve MCP tool calling, and having just discovered Monty — a new sandboxed Python runtime from Pydantic — I was motivated to spend a weekend building an example project to explore further. Standard LLM tool calling has a fundamental inefficiency: the model calls one tool at a time, waits for the result, decides what to call next, and round-trips back to the model for every step. For questions that require fetching data from multiple sources, time (and tokens) add up fast. The monty-example project explores a different approach: let the model write code that orchestrates tool calls and executes that code in a sandbox running within your code! ...

April 11, 2026 · 11 min · Michael OShea

Agentic Orchestration is Not a Moat

The recent explosion of social media frenzy over agentic orchestration tools such as OpenClaw and GasTown, vibe-coded and quickly released into the wild, is yet another symptom of overhyped expectations related to generative AI models. If it takes three weeks to go viral after a few months of vibe coding, it’s a trivial solution, and it will be copied, relentlessly, and everyone will move on to something else–not sure what that will be. ...

February 14, 2026 · 4 min · Michael OShea

Model Context Protocol (MCP) Best Practices

As we integrate services and data APIs into agentic AI solutions, interest is growing in how the Model Context Protocol (MCP) can standardize the way tools expose their capabilities to agents. With that in mind, I’ve assembled—yes, with the help of AI—a survey of key topics and resources related to MCP. MCP is an open standard (launched by Anthropic in Nov 2024) for exposing data sources, tools, and “resources” to AI agents via a uniform interface. It is designed to replace the ad-hoc “one-off connector per tool/agent” pattern, simplifying how LLM-based agents integrate with live systems. [1] ...

September 29, 2025 · 8 min · Michael OShea

A2A Doesn't need AI Agents

Is this just distributed computing re-packaged for AI? What is A2A Without AI Agents? I got into a debate with Gemini recently about Agent-To-Agent protocol (A2A). I said I thought it was a retread of existing distributed computing technologies like Service Discovery, Mesh, CORBA, etc. Perhaps Gemini took it personally, as Google (Gemini’s Creator) had announced A2A in April, and Gemini got a little “gushy” on how it was “a revolutionary new idea.” Also, perhaps “debate” is too strong a word. And I might want to consider getting out more often. ...

September 28, 2025 · 2 min · Michael OShea