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ContextForge.dev
Agentmemory
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.
Amazon CloudFront 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, Amazon CloudFront seems to be more popular. It has been mentiond 87 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.
Using a Content Delivery Network (CDN) like CloudFront to serve static assets faster. - Source: dev.to / 2 months ago
Semantic Caching: Cache similar queries' results using result fingerprinting. Edge caching via Amazon CloudFront for reduced latency. - Source: dev.to / 3 months ago
CloudFront may sound like Cloudflare, but it is an unrelated AWS service (https://aws.amazon.com/cloudfront/) (Disclaimer: I work for Cloudflare, which is not CloudFront). - Source: Hacker News / 3 months ago
In this post we are using an Amazon EC2 T3 Micro instance running Ubuntu with an nginx web server. We'll use AWS Systems Manager to help set up a CI/CD pipeline using GitHub Actions. We'll then configure AWS Certificate Manager with Amazon CloudFront and have it connected to our domain with Amazon Route 53! We'll be using a Vue Nuxt 4 application as our web app. - Source: dev.to / 5 months ago
A best practice for your web applications is to use Amazon S3 to store content and Amazon CloudFront to deliver it to users and protecting your data at rest and in transit. Encryption is one of protection controls AWS provides you to reduce the risks of unauthorized access, loss, or exposure. In this blog post, you will learn how to implement one of these options (SSE-KMS) in S3 when using CloudFront for content... - Source: dev.to / 6 months ago
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