Apollo.io
ZoomInfo
Lusha
Hunter.io
Instantly.ai
Clearbit
Snov.io
lemlist
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.
Apollo.io 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.
We use Apollo with our Sales and BDR team to manage our cold outreach. The strength of the platform is the sequences and cadences that you can set up. Compared to other tools we have used in the past like Salesloft the UI is much easier to navigate. The main limitation is that the quality of data isn't as vast and often I can find prospects on Linkedin but not in Apollo.
Based on our record, Apollo.io seems to be more popular. It has been mentiond 69 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.
Personal email domains destroy this. Clearbit's Enrichment API returns a null company when it hits gmail.com. Apollo routes personal domains straight to a consumer bucket and skips B2B fields entirely. Even PDL's /person/enrich endpoint โ the most permissive of the major providers โ gives you around 32% hit rate on Gmail addresses versus 74% on corporate domains. I measured this across 6,200 signups for a... - Source: dev.to / about 2 months ago
A few things worth flagging: PDL beats Clearbit's historical rates for US and Western European companies, but drops to ~52% match rate for Japan and South Korea specifically. Apollo underperforms on raw company matching but returns significantly more contacts per domain in Prospector-style queries than Clearbit's Prospector ever did โ the tradeoff is more stale titles in the result set. Hunter.io is fast and cheap... - Source: dev.to / about 2 months ago
One thing comparison guides consistently get wrong: Clay is not an enrichment API. It's a waterfall orchestration tool that calls People Data Labs, Apollo, Clearbit, and others in sequence for you. It's useful, but it adds 2โ8 seconds of latency per row in my runs and costs more per match than going direct. For a CRM webhook flow where you need sub-second enrichment calls, Clay is the wrong layer to hit first. - Source: dev.to / 3 months ago
Last year I ran the same LinkedIn Sales Navigator export through three enrichment APIs. Apollo matched 61% of the emails. Hunter.io matched 54%. An OSINT-first pipeline I'd built in n8n โ pulling from public sources before hitting any paid API โ matched 79% and cost roughly $0.003 per contact. The delta wasn't magic. It was sequence. - Source: dev.to / 3 months ago
Despite having its LinkedIn Page removed in 2025, Apollo remains a functional enrichment and outreach platform with 275M+ contacts. The free tier includes 10,000 credits and the $49/month basic plan is the cheapest entry point for a combined enrichment-plus-sequencing workflow. Apollo's data collection methods have attracted LinkedIn's attention, but the product continues to operate. The risk I'd assign it:... - Source: dev.to / 3 months ago
ZoomInfo - ZoomInfo is a B2B database providing detailed business information on people and companies.
Agentmemory - Persistent memory for Claude Code, Codex & coding agents
Lusha - Search less. Sell more.
OpenMemory MCP - Your private, local memory layer for all AI tools
Hunter.io - Find all the email addresses related to a domain
Instantly.ai - Build your own infinitely scalable cold email outreach system with Instantly.