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Stop re-explaining your project to Claude every session. ContextForge adds persistent memory to Claude Code, Cursor, and Copilot via MCP. Free tier, 3-minute setup.

Which is more popular?
Based on our record, ImportYeti should be more popular than ContextForge.dev. It has been mentioned 18 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | importyeti.com | contextforge.dev |
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| Platforms | — | |
| Company | — | Startup from the United States · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of ImportYeti yet.
ContextForge is persistent, searchable memory for AI coding agents — 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...
What each product offers, as listed by its team.


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How to Make Claude Run Automated Workflows (ContextForge Skills Tutorial)
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As answered by people managing ImportYeti and ContextForge.dev.
ContextForge.dev's answer:
ContextForge is memory that lives at the MCP layer, so it works across every AI coding agent at once — Claude Code, Cursor, GitHub Copilot, ChatGPT, and Windsurf — 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 — 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 — Claude Code, Cursor, GitHub Copilot, ChatGPT, Windsurf — 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 — 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.
Share your experience with using ImportYeti and ContextForge.dev. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


The shipment doesn't reference any baby products. BUT if you drill into their company's page on importyeti.com, one of their customers is Heritage Baby Products:. Source: about 3 years ago
Importyeti.com is another good resource. Source: over 3 years ago
Do a search on importyeti.com and see if it provides some clues. Source: almost 4 years ago
Init links the folder to a project, so every agent working in that repo reads and writes the same memory, and it adds the rules that make sessions check who else is live before big changes. For Cursor, Copilot, Claude Desktop and... - Source: dev.to / 17 days ago
I built ContextForge because I was losing this argument with my own agents several times a week. The idea is small: when we decide something, the agent saves the decision with the reason, in the project's memory. The next session, in... - Source: dev.to / about 1 month ago
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