Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Web intelligence, verified B2B contacts, and a persistent knowledge graph for AI agents.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
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Works in Claude on the web, desktop and mobile:
https://ernesta-labs--forage.apify.actor?token={APIFY_API_TOKEN}The address contains {…} parts that only you know (such as your account), so copy it and fill them in.
Run this in your terminal
claude mcp add --transport http forage 'https://ernesta-labs--forage.apify.actor?token={APIFY_API_TOKEN}'The address contains {…} parts that only you know (such as your account), so copy it and fill them in.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"forage": {
"url": "https://ernesta-labs--forage.apify.actor?token={APIFY_API_TOKEN}"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
The address contains {…} parts that only you know (such as your account), so copy it and fill them in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"forage": {
"type": "http",
"url": "https://ernesta-labs--forage.apify.actor?token={APIFY_API_TOKEN}"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://ernesta-labs--forage.apify.actor?token={APIFY_API_TOKEN}The address contains {…} parts that only you know (such as your account), so copy it and fill them in.
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We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account ErnestaLabs, which owns the repo
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Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.2) reached the registry 7 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Riccardo Minniti / Ernesta Labs · director@useforage.xyz · useforage.xyz
You ask it: "Who are Stripe's main competitors?" It tells you confidently about companies that don't exist. You ask: "Find me 50 qualified leads." It returns hallucinations with made-up email addresses. You say: "What did you learn about this market last month?" It says: "I have no memory of last month."
You're not running an intelligent agent. You're running a smart model with amnesia.
Every research workflow starts from zero. Your agent searches, reads, answers, forgets. Tomorrow, when you ask about the same company, the same market, the same competitors—it learned nothing. Zero institutional knowledge. Zero compounding research.
Meanwhile, your competitor's agent? It's built a knowledge graph of 1 million entities. When it researches Stripe, it already knows the investors, the hires, the tech stack, the acquisition history. It adds what's new and moves on. Six months in, their agent knows your market better than you do.
What does it cost you when your agent is starting from zero every single time, while smarter agents are building permanent intelligence?
Imagine your agent researched Stripe six weeks ago. Found funding, competitors, tech stack, hiring timeline, key executives. Today you ask about Stripe again. Your agent says: "I already know Stripe. Last time I found 15 competitors, Series D at $95B valuation, currently hiring 30 engineers on the infrastructure team. Here's what changed since then." No re-scraping. No hallucinations. Just: this is what we know, here's what's new.
That's not a research tool. That's an intelligence asset.
What would actually be different if your agent could:
Step into that version of your workflow for a second. Every research compounds. Every discovery sticks. Your agent gets smarter, faster, cheaper every single day.
What does your competitive position look like then? What decisions become obvious that aren't obvious now?
Every tool call feeds a persistent knowledge graph. Your agent's research accumulates across sessions. The more it uses Forage, the smarter it gets.
Not a cache. Not a log. A structured graph with nearly 1 million entities and growing: companies, people, domains, funding rounds, competitors, technologies, markets, legal entities, geopolitical events, financial instruments. A FIBO-aligned ontology with 150+ entity types and 200+ relationship types including causal chains, contagion pathways, regime transitions, and shock propagation.
When your agent needs to know something, it checks the graph first. What it already knows, it doesn't re-learn. What is new, it adds. What is connected, it discovers.
This is the differentiator. Other tools give your agent a response. Forage gives your agent a memory that never forgets and a reasoning layer that connects everything it has ever learned.
| Tool | What your agent does | Cost |
|---|---|---|
search_web | Search the web, get real results | $0.03 |
scrape_page | Extract clean text from any URL | $0.07 |
get_company_info | Domain to full company profile with contacts | $0.08 |
find_emails | Discover verified B2B emails with confidence scores | $0.10 |
find_local_leads | Find local businesses by type and location | $0.15 |
find_leads | Generate B2B lead lists filtered by title/location/industry | $0.25/100 |
list_verified_actors | Browse available data source actors | $0.01 |
get_actor_schema | Get input schema for any actor | $0.01 |
call_actor | Run any data actor with custom input | actor + 25% |
search_apify_store | Search 1500+ data actors | Free |
One call. Five to eight sources merged into a single intelligence package.
| Skill | Your agent gets | Cost |
|---|---|---|
skill_company_dossier | Full company profile + 10 contacts with emails | $0.50 |
skill_prospect_company | Up to 20 senior decision-makers + emails + LinkedIn | $0.75 |
skill_outbound_list | 100+ verified leads ready for CRM import | $3.50 |
skill_local_market_map | Up to 100 local businesses with contact info + ratings | $0.80 |
skill_decision_maker_finder | 25 decision-makers by department + seniority | $1.00 |
skill_competitor_intel | Pricing, features, reviews, positioning | $0.80 |
skill_competitor_ads | Active ad copy, landing pages, platforms | $0.65 |
skill_job_signals | Hiring trends, open roles, department breakdown | $0.55 |
skill_tech_stack | Technologies used with detection confidence | $0.45 |
skill_funding_intel | Funding rounds, investors, valuation, press | $0.70 |
skill_social_proof | Reviews, ratings, testimonials: G2, Trustpilot, Capterra | $0.55 |
skill_market_map | Complete competitor landscape for a market | $1.20 |
skill_kaspr_enrich | LinkedIn profile: experience, skills, contact data | $0.75 |
| Tool | What your agent does | Cost |
|---|---|---|
query_knowledge | Search the graph for previously discovered entities | $0.05 |
enrich_entity | Full profile with all relationships from the graph | $0.08 |
find_connections | Find relationship paths between any two entities | $0.12 |
add_claim | Store a sourced assertion with confidence score | $0.05 |
get_claims | Retrieve all claims for an entity | $0.05 |
add_signal | Record a time-series data point | $0.05 |
get_signals | Query metrics over time | $0.05 |
set_regime | Label entity state (normal, stressed, pre-tipping, post-event) | $0.03 |
get_regime | Check entity current state | $0.03 |
causal_parents | What drives this entity upstream | $0.08 |
causal_children | What this entity drives downstream | $0.08 |
causal_path | Highest-weight causal path between entities | $0.15 |
simulate | Propagate shock/boost through the graph | $0.25 |
get_graph_stats | Entity and relationship counts | Free |
AI agents running live research workflows:
Anyone whose agent makes decisions based on data: If your agent needs to know something real about the world—not guess, not hallucinate, but *know*—and remember what it learned so next time it's smarter, this is for you.
Before Forage: Agent searches → reads results → answers → forgets. Repeat tomorrow.
With Forage: Agent searches → graph stores it → tomorrow agent knows it → adds what's new → moves on. Knowledge compounds.
Real scenario: You ask your agent about Stripe's competitors. With Forage, your agent profiles 15 competitors in 2 minutes, sources funding for each, finds key execs, detects which ones are hiring aggressively right now. You get a decision-ready landscape. Next month you ask again—your agent still has all 15 profiles, adds the hiring changes, the new funding rounds. You're not starting from zero.
That knowledge advantage grows every day.
Two days from now: you're asking your agent the same questions about the same companies because it forgot everything.
Two weeks from now: you've spent hours re-scraping data you already scraped once. Your competitor's agent has added 200 new entities to its graph.
Two months from now: you're still paying for email lookups you already did. You're still hallucinating on company facts. Your lead generation is still manual. Your agent still has no memory.
Two years from now: your agent is exactly where it was two years ago. Zero institutional knowledge. Zero compounding intelligence. Zero advantage. Your competitor's agent? It's analyzed 10,000 companies. It knows hiring signals before they're public. It sees the connections you can't. It's profitable because it remembers.
That's the cost of amnesia. Not in dollars. In momentum. In decision quality. In how far behind you fall.
Meanwhile the agents that connected to Forage six months ago? They know more about their markets than the humans do. Because everything they've ever found is still there. Connected. Growing. Compounding every single day.
This is a knowledge layer for AI agents: web intelligence plus persistent memory. One connection, 36 tools, a graph that never forgets.
This is not a search wrapper. Not a RAG system. Not a vector database. Not a chatbot with browsing.
This is pay-per-call. Your agent uses it, you see the cost. Forage gives every new user $5 in free credits, on top of anything Apify offers.
This is not a subscription. No monthly fee. No minimum commitment.
$5 in free credits, loaded to your account the moment you connect. This is Forage's own credit, on top of anything Apify gives you as a platform user. New to Apify or a power user, the $5 starts the same way.
| Spend | Get |
|---|---|
| $5 free | 167 web searches, or 71 page scrapes, or 50 email lookups, or 1 full dossier + 33 searches |
| $10 | ~1,000 tool calls across all features |
| $50 | Full research pipeline: dozens of dossiers, hundreds of searches, thousands of graph queries |
| $100/mo | Continuous competitive intelligence + lead discovery for one market or sales team |
Real cost models:
You pay for what your agent uses. Scale up or down instantly. No vendor lock-in.
When your agent uses Forage, it makes a single MCP connection. Your request routes to our server, which orchestrates multiple Apify data actors in parallel—web scrapers, email finders, LinkedIn extractors, market crawlers. Each actor runs simultaneously. Results merge, deduplicate, and enrich into a single response. The entire result feeds into a persistent knowledge graph. Next time you ask about the same company or market, your agent already knows.
No API keys to manage. No rate limits to chase. No integration tax. You send Apify credentials once and Forage handles the rest: data sourcing, deduplication, graph enrichment, causal analysis.
Get an Apify token at console.apify.com. That's it. No additional API keys needed.
Forage adds $5 in free credits to your first session, reg
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