Itamar
Workflows by Itamar
Enrich company profiles with Explorium MCP and Claude AI for GTM research
# 🕵️ Company Research Agent (n8n + Explorium + LLM) This n8n workflow automates company research by combining Explorium’s MCP server, web scraping tools, and an AI agent. Results are written to a Google Sheet for easy use in GTM, product analysis, or competitive research. --- ## 🚀 What It Does Given a list of company domains or names, this workflow will: 1. Look up company information using: - 🧠 **LLM Agent** to guide the research - 🔎 **Explorium MCP Server** for firmographic & tech signals - 🌐 Website content and SerpAPI scraping (optional) 2. Extract key commercial details (see below) 3. Format the output in a consistent JSON structure 4. Update a connected **Google Sheet** with the enriched results --- ## 🧩 Extracted Fields Each company is enriched with: - `domain` - `linkedinUrl` - `has_free_trial` - `cheapest_plan` - `has_enterprise_plan` - `last_case_study_link` - `market` (e.g., B2B or B2C) - `integrations` (e.g., Slack, Hubspot, MySQL) - `enrichment_status` --- ## 📥 Input Sheet Format | input | |-------------| | Explorium | | n8n | | Apple | | ... | --- ## 📤 Output Sheet Format | domain | linkedinUrl | has_free_trial | cheapest_plan | has_enterprise_plan | last_case_study_link | market | integrations | enrichment_status | |--------------|----------------------------------|----------------|----------------|----------------------|-----------------------------|--------|---------------------------------------------------|-------------------| | Explorium.ai | https://linkedin.com/company/... | TRUE | 69 | TRUE | https://www.explorium.com | B2B | ["HubSpot", "Zapier", "Salesforce", ...] | done | | n8n.io | https://linkedin.com/company/... | TRUE | 20 | TRUE | https://n8n.io/case-studies | B2B | ["Slack", "Gmail", "MySQL", "Google Sheets", ...] | done | --- ## 🛠️ Tools Used - **n8n** (Automation platform) - **Explorium MCP Server** – rich company enrichment via API - **Anthropic Claude or OpenAI** – used by the AI researcher - **Google Sheets** – stores output data - **Structured Output Parser** – ensures clean, predictable JSON formatting --- ## 📦 How to Set It Up 1. Add your company domains or names to the input sheet 2. Configure your MCP and SerpAPI credentials in n8n 3. Run the workflow using the `Test Workflow` trigger 4. Watch the sheet populate with results You can adapt the system to output different formats or fields depending on your team's research goals. --- ## 📌 Use Cases - Competitive landscape analysis - Lead intelligence for outbound campaigns - Feature benchmarking (e.g., who offers enterprise or free trial) - VC/investment research --- ## 🧠 Notes - This agent is easily customizable. Adjust the LLM prompt or Output Parser to extract different properties. - Explorium MCP is leveraged as the **core enrichment engine**, ensuring signal accuracy and freshness.
Automate company ICP scoring with Explorium data and Claude AI analysis
# 🧠 ICP Scoring Agent (n8n + Explorium + LLM) This workflow automates Ideal Customer Profile (ICP) scoring for any company using a combination of Explorium data and an LLM-driven evaluation framework. --- ## 🔧 How It Works 1. **Input**: Company name is submitted via form. 2. **Data Enrichment**: Explorium's MCP Server is used to fetch firmographic, hiring, and tech data about the company. 3. **Scoring Logic**: An AI agent (LLM) applies a 3-pillar framework to assess and score the company. 4. **Output**: A structured JSON or Google Doc summary is generated using the AgentGeeks formatter. --- ## 📊 Scoring System (100 points total) | Pillar | Max Points | |------------------------------|------------| | Strategic Fit | 40 | | AI / Tech Readiness | 40 | | Engagement & Reachability | 20 | ### 🧠 Scoring Criteria - **Strategic Fit**: Industry, size, use case, buyer roles - **Tech Readiness**: AI maturity, hiring trends, stack visibility - **Reachability**: Geography, contactability, data quality --- ## 🎯 Verdict Scale - 🟩 **90–100**: Ideal ICP - ✅ **70–89**: Good Fit - 🟨 **40–69**: Medium Fit - ❌ **< 40**: Poor Fit --- ## 📦 Workflow Components - **Trigger**: Form submission via webhook - **MCP Client**: Pulls enriched company data via Explorium's MCP API - **AI Agent**: Uses Anthropic Claude (or other LLM) to calculate scores - **Output**: Results are posted to a structured endpoint (e.g. Google Doc or JSON API) --- ## 🧰 Dependencies - [n8n](https://n8n.io/) (self-hosted or cloud) - Explorium MCP credentials and access - LLM API (e.g., Anthropic Claude, OpenAI, etc.) - Optional: AgentGeeks formatter or similar doc generator --- ## 💼 Use Case This ICP scoring system is designed for GTM and sales teams to: - Automate lead prioritization - Qualify accounts before outbounding - Sync ICP data into CRMs, routing systems, or reporting layers --- ## 📈 Example Output in Google Doc ```json { "company": "Acme Inc.", "score": 87, "verdict": "Good Fit", "pillars": { "strategic_fit": 35, "tech_readiness": 37, "reachability": 15 }, "summary": "Acme Inc. is a mid-sized SaaS company with strong AI hiring activity and a buyer profile aligned to enterprise IT. Moderate reachability via firmographic signals." }