open-sales-stack

by ekas-io

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About

Collection of B2B sales intelligence MCP servers. Includes website analysis, tech stack detection, hiring signals, review aggregation, ad tracking, social profiles, financial reporting and more for AI-powered prospecting

Details

Author
ekas-io
Categories
Web Scraping, Other, Marketing

Setup

Install open-sales-stack in your MCP client (Claude Desktop, Cursor, Windsurf, and others).

Repository: https://github.com/ekas-io/open-sales-stack

Follow the installation instructions in the repository README, then restart your MCP client.

Open source MCP servers for B2B sales research — built byEkas

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.

An API key fromOpenAI, Anthropic, or Google Geminiis 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 frompython.orgor install viabrew install python@3.12
- An LLM API key— from
OpenAI,Anthropic, orGoogle 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 --all

By default, the script adds MCPs toClaude Codeif theclaudeCLI is available, otherwise toClaude 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.envautomatically.

If you want to change the default model later, edit theLLM_PROVIDERvalue in your.envfile. See.env.examplefor 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 thesocial-intel READMEfor more details.

bash scripts/add-to-claude.sh --website-intel --social-intel --hiring-intel

"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 Claudehowto use research data for sales workflows. Drop them into your Claude project knowledge or reference them in prompts.

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 thepackages/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 thepackages/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.

Identifies the sales and marketing tools a company uses from its website, returned as simple per-tool flags. Part of the Mamba Labs signal toolkit.

PredictLeads MCP lets AI agents securely access PredictLeads datasets - including jobs, news, funding, technologies, connections, and company data

B2B lead generation MCP server - Apollo, Google Maps, email finder, skip trace, and 15+ more tools.

Finds a company LinkedIn page from a domain or name and returns firmographics for enrichment workflows. Part of the Mamba Labs signal toolkit.

Detects whether a company is hiring for go-to-market roles by reading its ATS boards, returning a Clay-ready hiring signal. Part of the Mamba Labs signal toolkit.

MCP server for the B2B database service Limadata

Access Google Maps data, reviews, AI-structured insights, and business leads through the Outscraper MCP server, designed for seamless integration with AI agents and automation workflows.

Find buying signals for companies and contacts

B2B SaaS GTM stack intelligence — 17 tools spanning catalog search, overlap detection, n-way vendor comparison, decision-stage buyer questions, and renewal-negotiation playbooks.

Windsor MCP enables your LLM to query, explore, and analyze your full-stack business data integrated into Windsor.ai with zero SQL writing or custom scripting.

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