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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.
CouchDB 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, CouchDB seems to be more popular. It has been mentiond 25 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.
CouchDB has a "List function" feature which allows you to transform query results. - Source: dev.to / 7 months ago
CouchDB on the serer and PouchDB on the client was an attempt at making such an environment: - https://couchdb.apache.org/ - https://pouchdb.com/ Also some more pondering on local-first application development from a "few" (~10) years back can be found here: https://unhosted.org/. - Source: Hacker News / about 1 year ago
The author would be excited to learn that CouchDB solves this problem since 20 years. The use case the article describes is exactly the idea behind CouchDB: a database that is at the same time the server, and that's made to be synced with the client. You can even put your frontend code into it and it will happily serve it (aka CouchApp). https://couchdb.apache.org. - Source: Hacker News / over 1 year ago
That was my first thought! https://couchdb.apache.org/ is pretty good though is it still the incremental views with JS? - Source: Hacker News / over 1 year ago
In this post, I'll show how to simulate a multi-master synchronization with Apache CouchDB considering an off-line scenario. To reach this goal, I'll use Docker and Docker compose. - Source: dev.to / over 1 year ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Agentmemory - Persistent memory for Claude Code, Codex & coding agents
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
OpenMemory MCP - Your private, local memory layer for all AI tools
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.