
Apify
ScrapingBee
exa.ai
tavily
Browser Use
Scraper API
SerpApi
The web data API for AI agents

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, Firecrawl should be more popular than ContextForge.dev. It has been mentioned 6 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | firecrawl.dev | contextforge.dev |
| Pricing | ||
| Platforms | — | |
| Company | Startup from the United States | Startup from the United States · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


Firecrawl is the open-source web data API for AI agents. Search the web and get full-page results, scrape any URL (including JavaScript-heavy pages) into clean Markdown or structured JSON, crawl and map entire sites, parse PDFs and documents, and interact with dynamic pages. Free plan: 1,000...
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.


Possible disadvantages
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.
Turn AI Web Scraping into Profit (My Firecrawl & n8n System)
More videos
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 Firecrawl 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 Firecrawl 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.


It depends on the job. For turning known URLs into clean Markdown, a scraping API such as Spicrawl, Firecrawl or Jina Reader is the simplest. For crawling whole sites, Firecrawl, Crawl4AI, Context.dev and Apify follow...
Firecrawl is one of the most powerful tools for turning websites into clean, structured, LLM-ready data. It removes the complexity of traditional web scraping and provides a simple API that converts web pages into...
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.


# Find URLs on a site, ordered by relevance to a word Result = app.map("https://firecrawl.dev", search="pricing") # Scrape several URLs at once Job = app.batch_scrape([ "https://firecrawl.dev", "https://docs.firecrawl.dev", ],... - Source: dev.to / 12 days ago
Generate-lander.ts — This is the interesting one. It uses Anthropic + Firecrawl to scrape a partner's website, then generates a custom landing page for their affiliate program. Automated partner onboarding. - Source: dev.to / 6 months ago
My guy, there's an error in your app: Firecrawl API key missing or invalid. Set FIRECRAWL_API_KEY in .env.local to your key from https://firecrawl.dev — then restart `next dev`. - Source: Hacker News / 7 months 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 / 15 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 / 30 days ago
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