Ollama
LM Studio
Jan.ai
Hugging Face
LangChain
GPT4All
Claude AI
OpenAI
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.
Ollama ContextForge.devOllama is recommended for businesses and teams seeking an efficient project management solution. It is especially useful for remote teams, startups, and any organization looking to enhance collaboration and project tracking capabilities.
ContextForge.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, Ollama seems to be more popular. It has been mentiond 285 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.
The first step is getting Ollama on your machine. Visit ollama.com, click Download, and install the version for your operating system [2]. Once installed, verify itโs working by opening your terminal or Command Prompt and running:. - Source: dev.to / 2 days ago
I wanted an AI code reviewer that was 100% private, free, and actually understood the context of my entire project. So, I built one using Python and Ollama. - Source: dev.to / 3 days ago
Hi, you should try https://ollama.com/ which is imo the most convenient way to run local LLMs (assuming your hardware allows). - Source: Hacker News / 4 days ago
Agentic coding runs through Aider, configured to talk to local Ollama models by default and fall back to the free tiers on Groq and OpenRouter when a task wants more horsepower. Same agent, same workflow, whether it's fully offline or tapping a free hosted model. - Source: dev.to / 5 days ago
To see available tags for any model, check the model page on ollama.com or run ollama show llama3 --modelfile to inspect what you currently have. - Source: dev.to / 11 days ago
LM Studio - Discover, download, and run local LLMs
Agentmemory - Persistent memory for Claude Code, Codex & coding agents
Jan.ai - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs like OpenAIโs GPT-4 or Groq.
OpenMemory MCP - Your private, local memory layer for all AI tools
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.
LangChain - Framework for building applications with LLMs through composability