@bingeljell/lead-gen-mcp
Provides search capabilities for discovering companies using the Brave Search API.
Provides automatic fallback search for company discovery using DuckDuckGo.
Optionally uses OpenAI's LLM to improve the accuracy of company data extraction.
Provides search capabilities for company discovery via a self-hosted SearXNG instance.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@@bingeljell/lead-gen-mcp Find 10 MSPs in Austin, Texas and save their contact emails."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
@bingeljell/lead-gen-mcp
MCP server for AI-assisted B2B lead generation. Discover, extract, score, and export company leads — from any MCP-compatible agent (Claude Desktop, Cursor, Windsurf, Codex, etc.).
Context
This started as a lead pipeline inside Alfred — a personal AI agent built for outbound sales work
Extracted into a standalone MCP server so anyone selling to small and mid-sized businesses can use it with their agent of choice
Works across agents — not Claude-specific
Still under active development. See docs/release_notes.md for what's in each release
Related MCP server: leadOracle
Tools
Tool | What it does |
| Search for companies matching a query and rank them by ICP fit. No browser required. |
| Deep-extract a single company's name, emails, industry, and size from a URL via headless browser. |
| Full pipeline: search → rank → extract → filter → save to CSV. |
Requirements
Node.js ≥ 20
A search provider — SearXNG (self-hosted), Brave API key, or nothing (falls back to DuckDuckGo automatically)
An LLM key (Anthropic or OpenAI) — optional but improves extraction quality
Setup
Option A — Use via npx (no clone needed)
The server runs on demand. Just configure your agent to call it with npx:
"command": "npx",
"args": ["-y", "@bingeljell/lead-gen-mcp"]Option B — Clone and build locally
git clone https://github.com/bingeljell/lead-gen-mcp
cd lead-gen-mcp
npm install
npx playwright install chromium # one-time ~130MB browser download
npm run buildPoint your agent at the built file:
"command": "node",
"args": ["/absolute/path/to/lead-gen-mcp/dist/server.js"]Agent configuration
Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"lead-gen": {
"command": "npx",
"args": ["-y", "@bingeljell/lead-gen-mcp"],
"env": {
"SEARXNG_BASE_URL": "http://localhost:8888",
"ANTHROPIC_API_KEY": "sk-ant-...",
"LEAD_GEN_OUTPUT_DIR": "/Users/you/leads"
}
}
}
}Restart Claude Desktop. The three tools appear automatically.
Cursor / Windsurf
Same config format — add to your MCP settings JSON and restart the editor.
OpenAI Agents SDK (Codex)
from agents import Agent
from agents.mcp import MCPServerStdio
lead_gen = MCPServerStdio(
command="npx",
args=["-y", "@bingeljell/lead-gen-mcp"],
env={
"SEARXNG_BASE_URL": "http://localhost:8888",
"ANTHROPIC_API_KEY": "sk-ant-...",
"LEAD_GEN_OUTPUT_DIR": "./leads"
}
)
agent = Agent(name="LeadResearcher", mcp_servers=[lead_gen])Claude Code (CLI)
claude mcp add lead-gen \
-e SEARXNG_BASE_URL=http://localhost:8888 \
-e ANTHROPIC_API_KEY=sk-ant-... \
-e LEAD_GEN_OUTPUT_DIR=/Users/you/leads \
npx -y @bingeljell/lead-gen-mcpEnvironment variables
# Search — set at least one (falls back to DuckDuckGo if none set)
SEARXNG_BASE_URL=http://localhost:8888 # self-hosted SearXNG
BRAVE_SEARCH_API_KEY= # https://api.search.brave.com
# LLM — optional, improves extraction accuracy
ANTHROPIC_API_KEY=
OPENAI_API_KEY=
# Output directory for CSVs
LEAD_GEN_OUTPUT_DIR=./leadsCopy .env.example for a template.
ICP profiles
The profile parameter tunes candidate ranking for different buyer types:
Profile | Target |
| Any business |
| Managed service providers (IT/cybersecurity) |
| Systems integrators / Microsoft partners |
| Event planning / wedding businesses |
Example prompts
"Find 10 MSPs in Austin, Texas and save their contact emails."
"Search for small systems integrators in the UK, vertical msp_uk, max 5 leads."
"Discover event planning companies in Chicago — profile: event_planner."
License
MIT
Available Tools
3 toolslead_discoverB
Search for company candidates matching a query and rank them by ICP fit. Returns scored URLs ready for extraction — no browser required.
Inputs: query (required), country, profile, vertical, +1 more.
lead_extractA
Deep-extract company info (name, emails, industry, size) from a single URL using a headless browser and optional LLM parsing.
Inputs: url (required), deep.
lead_generateC
Full pipeline: search → rank → extract → filter → save to CSV. Returns a list of discovered leads with emails.
Inputs: query (required), vertical (required), country, filters, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 3 tools
Tools have distinct purposes: discovery, extraction, and full pipeline. The generate tool subsumes the other two but is a convenience layer, not a source of confusion. Minor overlap exists but descriptions clearly differentiate them.
All tool names follow a consistent lead_verb pattern (discover, extract, generate). The naming is predictable and aligns with tool function.
Three tools is on the lower end but appropriate for a focused lead generation server. Each tool earns its place, covering search, extraction, and pipeline integration.
The tool set covers the core lead generation workflow—search, extract, and output. Missing features like batch extraction or lead management are minor gaps for this scope.
Maintenance
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