nowfound

AI · May 12, 2026

Vulcanizare Mobilă

First AI-native roadside assistance API, open SDK, MCP ready

What it does

First roadside tire service marketplace with native AI integration via MCP (Model Context Protocol). Live in Romania with 95+ active partners, expanding to Italy. → AI agents (Claude, ChatGPT) autonomously dispatch technicians — zero human intervention → Public REST API v2 + open SDK on GitHub → Chrome & Firefox extensions → Built for fleets, insurers & drivers The same model is replicable in any country.

Does a similar job

all alternatives →
  • Opper AIJul 2026 · opper.ai · ▲229

    The european AI gateway for agents

  • Merge Agent HandlerOct 2025 · ▲321

    Power your AI agents with enterprise-ready tools via MCP

  • Apideck MCP ServerMay 2026 · apideck.com · ▲178

    Give AI agents access to real-time data across 200+ apps

  • API to MCPJun 2026 · apitomcp.ai · ▲195

    Turn any API into an MCP server for AI agents

  • Dawiso AI Context LayerJan 2026 · ▲82

    Connect AI agents to governed metadata via MCP

  • AP
    AI-powered web service combining FastAPI, Pydantic-AI, and MCP serversSep 2025 · github.com · ▲46

    Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…

More ai this month

the category →
  • I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.

    AI · 17d ago · simedw.com

  • Astute585

    Automate your B2B brand going viral, with new media creators

    AI · 19d ago · company-app.joinastute.com

  • Grok Bot547

    AI teammates that you can give real work to

    AI · 26d ago · x.ai

  • Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

    AI · 27d ago · cactuscompute.com

  • Monid475

    One wallet, every paid tool your agent needs

    AI · 7d ago · monid.ai

  • Turn website visitors into qualified pipeline

    AI · 20d ago · clarasdr.ai

Launched alongside, May 2026

the whole month →
  • Brew 905

    Like Claude design for email marketing

    AI · May 2026 · brew.new

  • Parallel agents, diff reviewer, and multi-model comparisons

    Dev tools · May 2026 · kilo.ai

  • StoreClaw805

    Grow your store profits with agents that know how to sell

    AI · May 2026 · storeclaw.ai

  • Give your agent a real number and voice to make calls.

    AI · May 2026 · pollyreach.ai

  • NW

    Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

    Life & fun · May 2026 · github.com

  • FM

    Dev tools · May 2026 · github.com