Open source MCP servers for B2B sales research — built by Ekas
Give Claude the ability to research companies and prospects using public web data.
Open Sales Stack contains MCP servers for sales research and skills that teach Claude how to use them in real workflows.
| 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 |
| 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.
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:
# 1. Clone the repo
git clone https://github.com/ekas-io/open-sales-stack.git
cd open-sales-stack
# 2. Run setup (installs everything and prompts you to choose your LLM provider)
bash scripts/setup.sh
# 3. Verify your setup
bash scripts/verify.sh
# 4. Add all MCPs to Claude
bash scripts/add-to-claude.sh --allBy default, the script adds MCPs to Claude Code if the claude CLI is available, otherwise to Claude Desktop. You can override this:
bash scripts/add-to-claude.sh --all --desktop # force Claude Desktop
bash scripts/add-to-claude.sh --all --code # force Claude CodeThe 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):
- Skip (default) — configure later; company scraping works without login
- Browser login — a browser window opens, you log in manually
- Credentials — provide your email + password, saved locally for headless login
See the social-intel README for more details.
If you only want specific MCPs:
bash scripts/add-to-claude.sh --website-intel --social-intel --hiring-intelOnce added, ask Claude:
"What MCP tools do you have access to?"
You should see your installed tools listed.
Each MCP is independent — use one or use all. But they're designed to chain naturally in Claude. Here's what a typical company research flow looks like:
You: "Research Acme Corp for me"
Claude calls: website-intel → scrapes acmecorp.com, extracts product info, pricing, team
Claude calls: techstack-intel → detects they use HubSpot, Drift, Segment
Claude calls: hiring-intel → finds 3 open SDR roles on their Greenhouse page
Claude calls: social-intel → finds their VP Sales on LinkedIn, pulls bio and recent posts
Claude calls: review-intel → pulls G2 rating (4.2/5, 47 reviews), Glassdoor sentiment
Claude calls: ad-intel → 12 active LinkedIn ad campaigns, 5 on Meta
Claude calls: funding-intel → Series B, $24M raised, led by Accel
Claude calls: firmographic-intel → 320 employees, 40% headcount growth YoY
Claude calls: news-intel → 3 recent press mentions, product launch last month
Claude: "Here's what I found about Acme Corp..."
You don't need to orchestrate this. Claude reads the tool descriptions and decides which to call based on your request.
Skills are instruction files that teach Claude how to use research data for sales workflows. Drop them into your Claude project knowledge or reference them in prompts.
| Skill | What it teaches Claude |
|---|---|
| Lead Qualification | Evaluate whether a company matches your ICP based on research signals |
| Prospect Research | Full account + contact level research methodology |
| LinkedIn Recon | Read a prospect's LinkedIn profile and posts for outreach signals |
| Cold Email Personalization | Turn research into personalized outreach copy |
MCPs get the data. Skills tell Claude what to do with it.
Every package has its own README with tool descriptions, input/output schemas, and usage examples. Browse the packages/ directory, or see detailed use cases on our website: ekas.io/open-sales-stack
Found a bug? Want to add a new research MCP? PRs welcome. See the packages/ directory for the existing pattern.
These tools cover common research workflows. If you need AI automation built for your team's specific sales stack — CRM integration, lead routing, qualification scoring, automated outreach — we build that.
ekas.io — AI engineering for B2B sales teams.
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