惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

The GitHub Blog
The GitHub Blog
有赞技术团队
有赞技术团队
Apple Machine Learning Research
Apple Machine Learning Research
V
V2EX
Engineering at Meta
Engineering at Meta
美团技术团队
H
Hackread – Cybersecurity News, Data Breaches, AI and More
博客园 - 司徒正美
I
InfoQ
S
SegmentFault 最新的问题
博客园 - 叶小钗
N
Netflix TechBlog - Medium
Y
Y Combinator Blog
IT之家
IT之家
博客园 - Franky
大猫的无限游戏
大猫的无限游戏
人人都是产品经理
人人都是产品经理
T
The Blog of Author Tim Ferriss
月光博客
月光博客
The Cloudflare Blog
U
Unit 42
GbyAI
GbyAI
L
LangChain Blog
Microsoft Azure Blog
Microsoft Azure Blog

Hacker News: Show HN

PurrrrrFocus: Pomodoro Timer App - App Store Workflow Engine — Multi-Step Orchestration for Bun RapidPhoto: Pro Photo Editor App - App Store GitHub - DheerG/swarms: Achieve extraordinary results with claude code across a variety of tasks SPICE simulation → oscilloscope → verification with Claude Code — Lucas Gerads Show HN: VCoding – A 5 MB native Windows IDE with no dynamic dependencies Show HN: LLMs don't hallucinate because they're bad at math, it's the format GitHub - Agent-FM/agentfm-core: AgentFM is a peer-to-peer network that turns everyday computers into a decentralized AI supercomputer. AgentFM lets you run massive AI workloads directly across a global mesh of idle CPUs and GPUs. Show HN: Tracking Top US Science Olympiad Alumni over Last 25 Years GitHub - Potarix/agent-hub: One place to talk to all your agents Show HN: Runtime security for AI agents(injection,tool abuse, data exfiltration) GitHub - dubeyKartikay/lazyspotify: Terminal Spotify client for macOS and Linux GitHub - the-banana-tool/king-louie: Easy to use GUI Personal AI Assistant. Win/Linux/Mac. Show HN I made my vacation rental bookable by AI agents–no Airbnb, 0% commission GitHub - basteez/jsf-autoreload: maven plugin to enable hot reload on jsf projects uvm32/hosts/host-gdbstub at main · ringtailsoftware/uvm32 GitHub - labsai/EDDI: Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus. GitHub - glitchnsec/fortyone-oss: AI Executive Assistant Platform Quickstart | Alien GitHub - muxshed/shed: One stream in, or many. Every destination, simultaneously. No cloud middleman, no per-channel fees, no limits. GitHub - ocrbase-hq/ocrbase: 📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. GitHub - impactjo/home-memory: MCP server that lets your AI assistant remember everything about your home. GitHub - Sets88/dbcls: DbCls is a powerful terminal database client that supports various databases GitHub - neptun2000/heor-agent-mcp GitHub - SeanFDZ/macmind: Single-layer transformer in HyperTalk for the classic Macintosh RollQuation: Math Puzzles - Apps on Google Play GitHub - dropbox/witchcraft Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis GitHub - opentalon/opentalon: OpenTalon is an open-source platform built from the ground up in Go as a robust alternative to OpenClaw LinkedIn™ 职位抓取工具 - Chrome 应用商店
Show HN: 2 weeks of coding, 3 months of OpenAI review, my...
Aldipower · 2026-04-28 · via Hacker News: Show HN

I run Tredict, an endurance sports training platform I've been building since 2020. OpenAI opened the ChatGPT App Directory to third-party submissions in December, and the official Tredict app is now live. The actual programming took me two weeks, but the entire process took three months.

AMA on the submission process to OpenAI (timeline, review effort, what they ask for), how I solved user-authenticated content inside the iframe widgets, or why I had to remove certain tools to stay on the fitness side of OpenAI's fitness/health line.

https://www.tredict.com/blog/tredict_chatgpt_app/

Connect with a free ChatGPT account in a couple of clicks, then ask ChatGPT to analyse your activities, rename past sessions, or create structured workouts. Planned workouts sync to Garmin, Coros, Wahoo, Suunto and some more via Tredict. When you ask for it, an interactive Tredict view opens directly in the chat thread, showing the actual activity with charts, map and metrics, or the structured workout you just created.

Two things I find interesting about this:

The app uses MCP UI Apps, not just tools. Tredict's actual activity and plan views render inside the chat as interactive widgets. Most ChatGPT apps I've seen so far are tool-only, the widget pattern is still uncommon. Getting user-authenticated content into those widgets was the hardest part. The widget runs in a sandboxed iframe that has no access to the user's OAuth tokens, and there are basically no documented best practices for this yet.

ChatGPT is also frugal with its context window, so it tends to fetch the activity list and skip the detailed metrics unless you nudge it. A vague "tell me about my run" gets a shallow answer, while "fetch the details and give me a detailed assessment" gets the full analysis. For multi-week plan creation Claude with the same MCP server still works noticeably better. With Claude.ai I can build full structured training plans spanning weeks or even months, with proper periodisation, mixed sport types and individualised intervals based on past activity data. ChatGPT struggles with that scope. The limit sits with the host, not the server. The interactive MCP UI Apps also work in Claude.ai, so the same activity and plan widgets render directly in the chat there too.

Server lives at https://www.tredict.com/api/mcp/v2 and works with any MCP-compatible host. Honestly it works best with Claude.ai, which makes it slightly absurd that my application to be listed in Anthropic's connector directory has been pending without feedback for a while. If any Anthropic folks see this: would genuinely appreciate a status update or even a rejection with reason.