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Alternatives

Products that do what Assemble Labs – Hardware Brain for LLMs/IDEs does

Hi HN friends, we're Nima (nimabanai) and Craig (cbschind) from Assemble Labs (https://assemblelabs.co) building the hardware context layer for AI to help you write better firmware faster. We’ve built an MCP server that plugs into any AI tool you’re using (Cursor, Claude Code, Gemini, etc.) and brings complete hardware context (schematics, datasheets, etc.) to your existing environment (new app fatigue is real...) with accuracy and in real time. Our goal is to make writing and debugging firmware on custom hardware faster and easier. Try out the free beta release:…

  1. 1

    Memory for your AI Tools

    2025

  2. 2
    Chiplab85

    Test firmware on a virtual chip with no hardware needed

    24d ago · veecle.ai

  3. 3

    Persistent AI memory across Claude Desktop & Cursor IDE

    Oct 2025

  4. 4

    The official Elevenlabs MCP Server

    2025

  5. 5

    Make AI IDEs even smarter with your team’s knowledge

    Sep 2025

  6. 6

    Give your app AI superpowers with MCPs

    2025

  7. 7MA

    I've been deeply involved in working with AI agents and large language models (LLMs) for a while now. During a recent job search, I found myself repeatedly explaining my skills and experiences to various assistants. Around the same time, I was creating content for my website to help hiring teams understand my capabilities better and make informed decisions. MCP had started to gain momentum and I saw a way to reduce my toil. So I built an MCP server that can effectively communicate my qualifications as a job candidate. This server acts as an AI-powered resume, providing an understanding of my…

    2025 · ai.jakegaylor.com

  8. 8

    Allow AI Agents to help you with Figma designs!

    Jan 2026

  9. 9

    Persistent memory for AI coding agents

    Apr 2026 · contextpool.io

  10. 10

    The fastest way to connect your data with your AI Tools.

    11d ago · mcp-builder.ai

  11. 11WM
  12. 12CI

    Hi, I'm Daniel from Zep. I've integrated the Cursor IDE with Graphiti, our open-source temporal knowledge graph framework, to provide Cursor with persistent memory across sessions. The goal was simple: help Cursor remember your coding preferences, standards, and project specs, so you don't have to constantly remind it. Before this integration, Cursor (an AI-assisted IDE many of us already use daily) lacked a robust way to persist user context. To solve this, I used Graphiti’s Model Context Protocol (MCP) server, which allows structured data exchange between the IDE and Graphiti's temporal…

    2025

  13. 13MS

    Hi HN! I built a custom MCP (Model Context Protocol) server that connects Blender to LLMs like ChatGPT, Claude, and any other llm supporting tool calling and mcps, enabling the AI to understand and control 3D scenes using natural language. You can describe an entire environment like: > “Create a small village with 5 huts arranged around a central bonfire, add a river flowing on the left, place a wooden bridge across it, and scatter trees randomly.” And the system parses that, reasons about the scene, and builds it inside Blender — no manual modeling or scripting needed. What it can do: -…

    2025 · blender-mcp-psi.vercel.app

  14. 14AM

    This is an open‑source Model Context Protocol (MCP) server that gives any LLM a sense of the passage of time. Most MCP demos wire LLMs to external data stores. That’s useful, but MCP is also a chance to give models perception — extra senses beyond the prompt text. Six functions (`current_datetime`, `time_difference`, `timestamp_context`, etc.) give Claude&#x2F;GPT real temporal awareness: It can spot pauses, reason about rhythms, and even label a chat’s “three‑act structure”. Runs locally in <60 s (Python) or via a hosted demo. If time works, what else could we surface? - Location &#x2F;…

    2025 · github.com

  15. 15CO

    I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…

    2025 · github.com

  16. 16MA

    Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https:&#x2F;&#x2F;github.com&#x2F;lastmile-ai&#x2F;mcp-agent) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and…

    2025 · github.com

  17. 17
    AutoMCP150

    Easily deploy your existing AI agent projects as MCP servers

    2025

  18. 18OS

    Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…

    2025

  19. 19
    Pensieve133

    Full company context for every AI agent

    Mar 2026

  20. 20IB

    We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…

    2025 · tinytpu.com

  21. 21

    The memory layer that decides what's worth remembering

    13d ago · skynetlab-cortex.com

  22. 22

    Give your agent tools to create beautiful, codebase-aware UI

    Apr 2026

  23. 23

    An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents. - fellowgeek/mcp-memory

    24d ago · github.com

  24. 24IM

    Hi HN! Ever wish you could just point your AI assistant at your terminal and say 'what's wrong with this output?' That's why I built iterm-mcp. It lets MCP clients like Claude Desktop directly interact with your iTerm2 terminal - reading logs, running commands, using REPLs, and helping debug issues. Want to explore data or debug using a REPL? The AI can start the REPL, run commands, and help interpret the results. This is an MCP server that integrates with Claude Desktop, LibreChat, and other Model Context Protocol compatible clients.…

    2025 · github.com

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