
Otterly.AI
Profound
Am I on AI
Ahrefs
Attensira
Diploria AI
Promptwatch
AI SEO Search Visibility & AI Rank Tracking Platform for LLM Search Engines like ChatGPT - GEO/AEO/LLMO

Agentmemory
Mem0
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, ContextForge.dev seems to be more popular. It has been mentioned 2 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | llmrefs.com | contextforge.dev |
| Pricing | ||
| Platforms | — | |
| Company | Startup from the United Kingdom · 1 - 9 employees · 2025 | Startup from the United States · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


LLMrefs is an AI search analytics platform that tracks brand visibility across generative AI search engines. It shows whether AI assistants like ChatGPT, Perplexity, and Gemini mention your brand when users ask questions about your industry. Supported AI Search Engines LLMrefs monitors 11...
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.


An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
LLMrefs - AI SEO Keyword Rank Tracker for LLM Search Engines
How to Make Claude Run Automated Workflows (ContextForge Skills Tutorial)
More videos
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing LLMrefs and ContextForge.dev.
LLMrefs's answer
Track keywords, not prompts Most AI SEO tools make you manage individual prompts. LLMrefs lets you add keywords and automatically generates prompt variations based on real conversations users have with AI chatbots. This saves time and produces more realistic results.
Statistical significance, not magic numbers Many competitors show vague "visibility scores" that are hard to interpret. LLMrefs uses transparent metrics like Share of Voice and Position. Results are aggregated and weighted across every prompt variation to ensure statistical significance.
Affordable with no hidden fees LLMrefs Pro is $79 per month and includes all 11 AI search engines. Competitors often charge extra per engine or have tiered pricing that gets expensive quickly.
Agency-friendly from day one One subscription covers unlimited projects and unlimited team members. Agencies do not need to buy separate accounts for each client.
Data quality focus LLMrefs emphasizes being the only platform that takes data quality seriously. They continuously check prompts and only report results when they have enough data to be statistically significant.
Comprehensive engine coverage Eleven AI search engines tracked in one dashboard. You do not need separate tools for ChatGPT, Perplexity, Google AI Overviews, and others.
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:
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:
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 LLMrefs and ContextForge.dev. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


On prompts: LLMrefs builds them from your keywords, GeoSuite generates them from your brand and market, and Profound's trial uses a fixed set. Everyone else lets you type the questions your customers actually ask.
We have no reviews of ContextForge.dev yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


Tracking LLMrefs since May 2025.
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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