I Built a Free Alternative to ZoomInfo's API for AI Agents

John Dukes — Tue, 24 Mar 2026 15:55:53 +0000

If you've ever tried to add real-time business intelligence to an AI agent, you've probably hit the same wall I did: enterprise APIs cost a fortune and aren't designed for the way developers actually build today.

ZoomInfo: $15K-30K/year, requires a sales call to even see pricing.
Crunchbase Enterprise API: $10K+/year, rate limits that don't work for agents.
PitchBook: $20K+/year, gated behind institutional access.

I needed something different. A developer-first API that gives AI agents access to real-time business events -- funding rounds, acquisitions, executive hires, contracts -- with actual AI scoring on top. And ideally, a free tier that's actually useful.

So we built FundzWatch.

What it does

FundzWatch has analyzed millions of business events going back to 2017. The API returns structured JSON for:

Funding rounds -- amount, stage, investors, date
Acquisitions -- acquirer, target, terms
Executive moves -- person, role, company
Government contracts -- agency, value, awardee
Product launches -- company, product, category

On top of the raw events, there's an AI scoring engine that analyzes signals and returns buyer intent scores (0-100), buying stages, inferred pain points, and specific outreach angles.

The pricing comparison

Feature	ZoomInfo	Crunchbase Enterprise	FundzWatch Free	FundzWatch Pro
Annual cost	$15K-30K	$10K+	$0	$588/yr
API calls	Varies	Varies	1,000/mo	10,000/mo
AI scoring	No	No	Yes	Yes
Buyer intent	Pageview-based	No	Event-based	Event-based
MCP server	No	No	Yes	Yes
CrewAI/LangChain tools	No	No	Yes	Yes
Credit card required	Yes	Yes	No	Yes
Sales call required	Yes	Yes	No	No
Event types	Limited	Funding only	5 types	5 types
Historical data	Varies	2013+	2017+	2017+

Python SDK

pip install fundzwatch

from fundzwatch import FundzWatch

fw = FundzWatch()  # uses FUNDZWATCH_API_KEY env var

# Get AI-scored leads
leads = fw.get_leads(min_score=60, max_results=10)
for lead in leads["signals"]:
    print(f"{lead['company_name']}: {lead['score']}/100")
    print(f"  Buying stage: {lead['buying_stage']}")
    print(f"  Outreach angle: {lead['outreach_angle']}")

# Get raw events
events = fw.get_events(types="funding", days=7)
for event in events["events"]:
    print(f"[{event['type']}] {event['title']}")

# Market overview
pulse = fw.get_market_pulse()
p = pulse["pulse"]
print(f"This week: {p['funding']['count_7d']} rounds, "
      f"${p['funding']['total_raised_7d'] / 1_000_000:.0f}M raised")

MCP Server (for Claude Desktop, Cursor, etc.)

If you use Claude Desktop or any MCP-compatible client, you can give your AI assistant direct access to FundzWatch data. No code needed.

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "fundzwatch": {
      "command": "npx",
      "args": ["-y", "@fundzwatch/mcp-server"],
      "env": {
        "FUNDZWATCH_API_KEY": "your_key_here"
      }
    }
  }
}

Then just ask Claude: "Who raised a Series B this week?" and get real, accurate answers from live data.

CrewAI Integration

from fundzwatch import FundzWatch
from fundzwatch.tools.crewai import get_fundzwatch_tools
from crewai import Agent, Task, Crew

fw = FundzWatch()
tools = get_fundzwatch_tools(fw)

researcher = Agent(
    role="Sales Intelligence Analyst",
    goal="Find high-intent companies that match our ICP",
    tools=tools,
)

task = Task(
    description="Find the top 10 companies most likely to buy right now. "
    "Focus on recent funding or leadership changes, score above 60.",
    expected_output="Ranked list with scores, stages, and outreach angles.",
    agent=researcher,
)

crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()
print(result)

The SDK also includes LangChain tool integrations (pip install fundzwatch[langchain]).

REST API

If you're not using Python, the REST API works with anything:

# Get funding events from the last 7 days
curl https://api.fundz.net/v1/watch/events?types=funding&days=7 \
  -H "Authorization: Bearer YOUR_API_KEY"

# Get AI-scored leads
curl -X POST https://api.fundz.net/v1/watch/signals \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"min_score": 60, "max_results": 10}'

Why I built this

Most business intelligence APIs were designed for enterprise sales teams with big budgets and long procurement cycles. They don't work well for:

AI agents that need structured, real-time data via simple API calls
Solo developers who can't justify $10K+/year for business data
Startups that need sales intelligence but aren't enterprise-scale yet

FundzWatch is built API-first for the AI agent era. The MCP server, CrewAI tools, and LangChain integrations exist because that's how developers are actually building sales intelligence today.

Get started

Free API key (no credit card): fundzwatch.ai/onboarding

Python SDK: pip install fundzwatch

MCP server: npx -y @fundzwatch/mcp-server

GitHub:

If you have questions or feature requests, drop a comment. I read all of them.

DEV Community: John Dukes