ekas-io/open-sales-stack

**Open source MCP servers for B2B sales research — built by Ekas**
Give Claude the ability to research companies and prospects using public web data.
---
What's in here
Open Sales Stack contains MCP servers for sales research and skills that teach Claude how to use them in real workflows.
MCP Servers
| MCP Server | What you get | Status |
|---|---|---|
| **website-intel** | Product info, pricing, team pages, company details — extracted as structured data from any website | ✅ Ready |
| **techstack-intel** | CRM, marketing automation, analytics, chat, support tools — detected from page source | ✅ Ready |
| **social-intel** | LinkedIn company profiles, people profiles, company posts | ✅ Ready |
| **hiring-intel** | Open roles across Indeed, LinkedIn, Glassdoor, Google Jobs, ZipRecruiter, and direct careers pages | ✅ Ready |
| **ad-intel** | Active campaigns, ad creatives, targeting signals — from LinkedIn Ad Library and Meta Ad Library | ✅ Ready |
| **review-intel** | Star ratings, review counts, pros/cons themes — from G2, Capterra, and Glassdoor | 🔄 In Progress |
| **funding-intel** | Funding rounds, investors, total raised, valuations — from Crunchbase and public filings | 🔄 In Progress |
| **news-intel** | Recent press coverage, product launches, leadership changes, M&A activity | 🔄 In Progress |
| **financial-reporting-intel** | 10-K/10-Q filings, revenue, growth rate, operating margins, guidance — for public companies | 🔄 In Progress |
| **firmographic-intel** | Employee count, headcount growth, HQ location, founding year, industry, SIC/NAICS codes, legal entity name — all from public sources | 🔄 In Progress |
| **github-intel** | Public repos, stars, contributors, commit activity, open issues, tech stack signals — from GitHub public API | 🔄 In Progress |
Skills
| Skill | What it does | Status |
|---|---|---|
| **Qualify High Inbound Volume** | Researches accounts across 5 signals (website, SDR hiring, LinkedIn ads, funding, product launches) to qualify whether they have high inbound lead volume — saves results to Apollo | ✅ Ready |
An API key from **OpenAI, Anthropic, or Google Gemini** is required for LLM-based extraction. Beyond that, no additional API keys are needed.
Each MCP runs locally on your machine. Your IP, your requests — no proxy infrastructure, no rate limiting concerns.
---
Setup
You'll need two things installed before starting:
- **Python 3.10+** — download from python.org or install via brew install python@3.12
- **An LLM API key** — from OpenAI, Anthropic, or Google AI Studio
Then run these commands in your terminal:
By default, the script adds MCPs to **Claude Code** if the claude CLI is available, otherwise to **Claude Desktop**. You can override this:
The setup script will ask you to choose between OpenAI, Anthropic, or Gemini and prompt for your API key. It configures everything in .env automatically.
If you want to change the default model later, edit the LLM_PROVIDER value in your .env file. See .env.example for supported format.
During setup, you'll also be asked how you'd like to authenticate with LinkedIn (for social-intel):