Pi MCP Codemode AI Agents JavaScript Tool Orchestration OpenAI Responses API Agents API Tool Search Function Calling MiroThinker Agent LLM Long-Horizon Reasoning Context Management Fault Tolerance

“You Said No MCP!”

Source: “You Said No MCP!” — Earendil Author: Earendil Engineering · Originally published: September 29, 2026 Reprint note: The English article below is reproduced from the supplied PDF, with its original wording and links retained. The session replay has been completed using the supplied transcript; visit the source for the interactive replay. Statements about product behavior reflect the original publication date. If you went to pi.dev in the past, you found a proud declaration that Pi does not support MCP. If you listen to podcasts where we talked about Pi, you will have found more than one dismissive statement about MCP from us. Including a post by Mario about it. And yet, if you upgrade to Pi you will find MCP is now a supported piece of functionality. What happened? ...

September 30, 2026 · 8 min · 1652 words · Earendil Engineering

OpenAI Tool Search: Load Large Tool Catalogs on Demand

Source: OpenAI API documentation — Tool search Editorial note: This is an independently published companion to the official guide. It preserves the technical structure and key examples in a condensed form. The official documentation remains the canonical and most current reference. As an agent’s tool catalog grows, loading every definition into the model context becomes expensive. Parameter schemas consume input tokens even when the associated tools are irrelevant to the current task, and changing those definitions can invalidate a cached prompt prefix. ...

September 11, 2026 · 9 min · 1831 words · OpenAI

In-Depth Analysis of MiroThinker 1.7: Engineering Optimizations and Guardrails for Long-Horizon Reasoning Agents

MiroThinker 1.7 has achieved SOTA results in the field of long-horizon question reasoning. These outstanding results stem from the combination of a powerful Model and a solid Harness. This article documents key engineering optimizations in its Harness implementation. Prerequisite Background MiroThinker is a deep research Agent — given a complex question (“what are the titles of the cs papers on arxiv today”), it autonomously breaks down the task, searches, scrapes webpages, runs Python for verification, and finally outputs the \boxed{answer}. The foundation is classic ReAct: each turn involves LLM reasoning + tool calling, the results are written back to the history, looping 200~300 times until convergence. ...

April 29, 2026 · 10 min · 1954 words · Simon Sun