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ContextForge.dev
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OpenMemory MCP
ContextForge is persistent, searchable memory for AI coding agents โ built on the Model Context Protocol (MCP).
Your AI assistant forgets everything when the session ends. ContextForge fixes that: save architectural decisions, naming conventions, and debugging context once, and any MCP client recalls it later with semantic search โ across sessions and across projects.
Works with: Claude Code, Claude Desktop, Cursor, GitHub Copilot, ChatGPT, and Windsurf.
Zephyr ContextForge.devContextForge.dev's answer:
ContextForge is memory that lives at the MCP layer, so it works across every AI coding agent at once โ Claude Code, Cursor, GitHub Copilot, ChatGPT, and Windsurf โ not just one. Save a decision once and any client recalls it later with semantic search. It goes beyond a note store: automatic git sync turns your commits and PRs into searchable knowledge, plus task tracking, snapshots, and team sharing โ all through a single MCP server you add with one command.
ContextForge.dev's answer:
Most memory tools are tied to a single agent or are just a key-value store. ContextForge is MCP-native, so it's portable across all your AI tools; it adds git sync so your codebase history becomes searchable context automatically; and it includes team features (shared spaces, collaborators) that solo-memory tools lack. Setup is one command, there's a genuine free-forever tier with no credit card, and paid plans start at just $9/month.
ContextForge.dev's answer:
Software developers and engineering teams who use AI coding assistants โ Claude Code, Cursor, GitHub Copilot, ChatGPT, Windsurf โ and are tired of re-explaining their project, architecture, and conventions every session. It fits solo developers working across multiple projects as well as small teams that need shared, persistent context.
ContextForge.dev's answer:
ContextForge was born from a simple frustration: AI coding agents forget everything the moment a session ends. Every new conversation meant re-explaining the same architecture, naming conventions, and past decisions. ContextForge was built to give AI agents a permanent, searchable memory through the Model Context Protocol โ so knowledge is captured once and reused forever, across sessions and projects. It even dogfoods its own memory to help build itself.
ContextForge.dev's answer:
Next.js 16 (App Router), React and Tailwind CSS for the dashboard, hosted on Vercel. Supabase (PostgreSQL) with pgvector powers the semantic vector search, and Deno edge functions serve the API. Embeddings use OpenAI text-embedding-3-small. The MCP client is a Node.js package (contextforge-mcp) on npm, implementing the Model Context Protocol.
Based on our record, Zephyr seems to be more popular. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Combining the Zephyr RTOS stack, running on an affordable nRF52840 Dongle with the power of modern web technologies turned out quite well and it has also allowed us to experiment with multiple subgroups, supported by the specs, but not yet by many devices in the market (at the time of writing at least - be sure to keep an eye out for that!). - Source: dev.to / over 1 year ago
Also, it's really great to see that the RFcreations mini-moreph and blueSpy software was able to capture and render this slightly more advanced source and that it was possible to build using Zephyr RTOS and the nRF52840 Dongle. - Source: dev.to / over 1 year ago
The Zephyr RTOS contains some great Bluetooth LE Audio related samples. One of them is the Basic Audio Profile (BAP) Broadcast Source sample. - Source: dev.to / over 1 year ago
I thought about what would be a good first capture, and remembered, I recently made a very simple Bluetooth Low Energy demo using Zephyr and Web, covered in an earlier post. - Source: dev.to / over 1 year ago
Check out Zephyr OS and Platform IO. Zephyr is part of the Linux foundation and has similarities to Linux with how it performs hardware abstraction (device tree). Platform IO integrates with other frameworks including mbed and Arduino. Source: almost 3 years ago
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