MCP has stopped being an experimental acronym. Claude, ChatGPT and Cursor can all connect to one server and ask it real questions about your data, instead of switching tabs. The interesting question is no longer "should I expose my data through MCP?" but "which of the three servers actually fits?" — Enginy, Amplemarket and the one we work on, ClawStud MCP. Each one is built for a different shape of work, and each one covers part of the picture that the other two do not.
What an MCP server for sales data is supposed to do
In the simplest case, you give Claude a token, point it at an endpoint, and from then on "what was last week's traffic?" turns into a real answer with numbers from your own store, instead of a polite guess. Three things have to be true for that to work: the server must hold your real data behind an authentication layer, it must expose that data as concrete tools an LLM can call, and the tools must describe what they return clearly enough that the model picks the right one. Most marketing copy skips the second and third, which is why most MCP connections feel like demo screens rather than actual work.
The honest side-by-side
"Honest" is the key word. Each of the three is built around a different product. Enginy is a sales-engagement platform with its own OpenAPI auto-generation. Amplemarket is a sales-engagement platform oriented to prospecting at scale. ClawStud is a shared client dashboard for agencies, sitting on top of GA4, Search Console and Stripe. The differences that matter for the LLM are not aesthetic — they decide what questions the model can actually answer.
| Capability | ClawStud MCP | Enginy MCP | Amplemarket MCP |
|---|---|---|---|
| Auth | Bearer token (csk_…) with per-tool scopes, or OAuth 2.0 + PKCE for ChatGPT and Claude connectors | OAuth 2.0 + PKCE | OAuth (per their docs); docs endpoint also open without a token |
| Tool definition source | Hand-curated, one tool per common sales question | Auto-generated from the OpenAPI spec | Auto-generated from the Amplemarket API |
| Tools exposed | 28: 27 read-only plus one that only saves social post drafts (GA4, Search Console, Stripe, Resend, PostHog, Vercel / Netlify, Supabase, plus per-workspace P&L). Tools cover period-over-period diffs (compare_periods), connection status (list_integrations), an alerts watchdog (list_alerts + get_alert), workspace profit after Stripe fees and operating expenses (get_workspace_pnl), and a metric dictionary (explain_metric) so the LLM does not invent definitions. | Mirrors the Enginy OpenAPI surface | 3 tools against the public docs KB (search_amplemarket_api, query_docs_filesystem_amplemarket_api, submit_feedback); the product API is behind OAuth and not in the public endpoint |
| Writes allowed | One: create_social_draft saves a draft; only a person can approve it, and nothing is published automatically | Both, depending on tool | Both, depending on tool |
| Multi-client / multi-workspace | Native. One token, many workspaces, per-tool scopes | One company per OpenAPI mapping | Sales-rep / sequence oriented |
| Pricing tier where it sits | Available on every plan including Free | Requires a paid Enginy seat (Smart plan: ~799 €/month, list price on Capterra) | Requires a paid Amplemarket seat |
| Onboarding included | No dedicated sessions needed; "Connect it in one command" | 5 onboarding sessions per plan | Varies; typically sales-led |
| Risk of an LLM taking action by mistake | Low: the model can only add a draft to a review queue; approving it needs a signed-in person | Medium: write tools can be reached | Medium: write tools can be reached |
Where ClawStud fits
You run an agency with several online-store clients. Each one already has GA4, Search Console, Stripe and a Resend account. You want the team to ask Claude or ChatGPT questions about any client without sharing master passwords, and without the model taking action by accident. ClawStud MCP was designed for that. The token never grants write access; per-tool scopes decide what an LLM sees; "list my clients" or "describe this workspace" lets the same connection span many stores. A solo founder running one store also fits, because every plan ships with it.
Where Enginy fits
You run a sales team of five to ten SDRs whose job is outbound. You want the model to look up a contact, check whether the reply indicated interest, or pull a sequence into a draft. Enginy was built for that and their MCP rides on the same OpenAPI their web app uses, which is the right call for a product with hundreds of endpoints. For that scale of sales operation the €1,500–3,000 monthly seat (Smart / Business) is the cost of doing business, not a margin problem.
Where Amplemarket fits
You prospect at volume and want the LLM to enrich lists, score replies, draft outreach and route hot leads to a human. Amplemarket is the right shape for that. Their MCP endpoint that anyone can hit today, however, exposes the knowledge base of the Amplemarket API documentation rather than the product itself: three read-only tools (search the API KB, query a read-only virtual filesystem with the docs, submit feedback). Their product API is reachable through OAuth but is not in the publicly listed tool set, and the difference matters when you actually want the model to pull a real prospect, not to look the API up. It is also a poor fit for "what changed on the site this week and is it consistent with what was paid for ads" — that is read-side revenue analytics, not prospect-side actions.
What ClawStud does not do (kept short on purpose)
Two things Enginy and Amplemarket can do that ClawStud cannot: send emails on behalf of a sender, and enrich a contact with emails and phone numbers. Both rely on a sales-engagement product; ClawStud is a dashboard, not an outbound engine. If those are your MCP requirements, stay on Enginy or Amplemarket. If "talk to my clients' analytics and revenue" is the requirement, ClawStud MCP is the only one of the three whose tools actually describe the answers.
How to decide in five minutes
If your team runs outbound at scale, with people to onboard and sequences to generate, look at Enginy or Amplemarket first. If your team is an agency or solo founder who needs a dashboard an LLM can interrogate on top of GA4, Search Console and Stripe, connect ClawStud MCP with one command and a token you create in Settings → API keys. The whole setup is two minutes and free. If it does not fit, you will know before lunch.
Technical reference: modelcontextprotocol.io — the open protocol that every one of these three servers implements.
Read next: How ClawStud MCP came to exist.
