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open-sales-stack

open-sales-stack

by 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.

OSS github Demo


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.


Related MCP server: Meta Ads MCP

Setup

You'll need two things installed before starting:

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 --all

By 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 Code

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):

  1. Skip (default) — configure later; company scraping works without login

  2. Browser login — a browser window opens, you log in manually

  3. 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-intel

Verify in Claude

Once added, ask Claude:

"What MCP tools do you have access to?"

You should see your installed tools listed.


How the MCPs work together

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

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.


Each MCP in detail

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


Contributing

Found a bug? Want to add a new research MCP? PRs welcome. See the packages/ directory for the existing pattern.


Custom sales automation

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.


License

MIT

Available Tools

1 tool
website_intel_extractA

Scrape or crawl a webpage and extract structured data as JSON using a custom schema. Use this tool when you know the specific URL of a website and need to extract particular information in a well-defined, structured format.

Two modes are available: • 'scrape' (default) — single-page extraction with full JS rendering. • 'crawl' — multi-page extraction that follows links up to a page limit.

You MUST provide three things:

  1. The target URL

  2. A JSON Schema object defining the exact shape of the data you want returned

  3. A natural-language prompt describing what to extract

Inputs: url (required), prompt (required), schema (required), mode, +1 more. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.1/5.0

    Scored across 1 tool

    Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or confusion. The tool's purpose is clearly defined.

    Naming Consistency5/5

    The single tool uses a clear snake_case name that follows a verb_noun pattern, which is consistent and readable.

    Tool Count1/5

    The server is named 'open-sales-stack', implying a broad sales automation toolkit, but provides only a single web scraping tool. This is a severe mismatch between scope and tool count.

    Completeness1/5

    The server offers only webpage extraction, leaving out essential sales stack functionalities such as lead management, CRM integration, or deal tracking. The tool surface is severely incomplete for the implied domain.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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