A production-grade lead generation MCP server using FastMCP, Crawl4AI and external enrichment services
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# Lead Generation Server Documentation    ## Table of Contents 1. [Overview](#overview) 2. [Features](#features) 3. [Architecture](#architecture) 4. [Prerequisites](#prerequisites) 5. [Installation](#installation) 6. [Configuration](#configuration) 7. [Running the Server](#running-the-server) 8. [API Documentation](#api-documentation) 9. [Examples](#examples) 10. [Advanced Configuration](#advanced-configuration) 11. [Troubleshooting](#troubleshooting) 12. [Contributing](#contributing) 13. [License](#license) 14. [Roadmap](#roadmap) 15. [Support](#support) --- ## Overview <a name="overview"></a> A production-grade lead generation system built on: - **MCP Python SDK** for protocol-compliant AI services - **Crawl4AI** for intelligent web crawling - **AsyncIO** for high-concurrency operations Implements a full lead lifecycle from discovery to enrichment with: - UUID-based lead tracking - Multi-source data aggregation - Smart caching strategies - Enterprise-grade error handling --- ## Features <a name="features"></a> | Feature | Tech Stack | Throughput | |---------|------------|------------| | Lead Generation | Google CSE, Crawl4AI | 120 req/min | | Data Enrichment | Hunter.io, Clearbit [Hubspot Breeze] | 80 req/min | | LinkedIn Scraping | Playwright, Stealth Mode | 40 req/min | | Caching | aiocache, Redis | 10K ops/sec | | Monitoring | Prometheus, Custom Metrics | Real-time | --- ## Architecture <a name="architecture"></a> ```mermaid graph TD A[Client] --> B[MCP Server] B --> C{Lead Manager} C --> D[Google CSE] C --> E[Crawl4AI] C --> F[Hunter.io] C --> G[Clearbit] C --> H[LinkedIn Scraper] C --> I[(Redis Cache)] C --> J[Lead Store] ``` --- ## Prerequisites <a name="prerequisites"></a> - Python 3.10+ - API Keys: ```bash export HUNTER_API_…
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