Newsletrix runs a built-in MCP server. Connect ChatGPT, Claude, or Cursor and your AI assistant can read your tracked newsletters, brand stats, and recommendations on demand. No exports. No copy-paste. No hallucinated numbers.
The Model Context Protocol is an open standard for letting AI assistants talk to external tools and data. Newsletrix implements it so the assistant you already use can answer questions about your real newsletter analytics, not a generic web search.
"Summarize last week's competitor sends." "Which brands are running discount campaigns?" "Show me the highest-scoring subject lines." Newsletrix turns the request into structured queries against your account.
The assistant only sees what you've tracked. Numbers come from your dashboard, not from training data. If a fact is in Newsletrix, it can quote it. If it isn't, it won't make one up.
No second dashboard to learn. Live inside Claude Desktop, the ChatGPT connectors panel, or Cursor's chat. Newsletrix is just another capability your assistant can reach for.
Each connection uses a scoped bearer token you generate in settings. Set an expiry, name it per device, revoke it when you're done. Nothing happens behind your back.
Seven structured tools the AI can invoke automatically. No prompt engineering required.
| Tool | What it returns | Use case |
|---|---|---|
| list_newsletters | Paginated list of newsletters in your account, with subject, brand, and effectiveness score. | Browse |
| get_newsletter | Full analysis for a specific send: SWOT, recommendations, scores, tone, compliance. | Detail |
| search_newsletters | Search by subject line or brand name across your tracked sends. | Search |
| get_brands | Every brand you track with aggregate metrics: avg open, CTR, effectiveness, last send. | Aggregate |
| get_dashboard_stats | High-level account stats: total sends, average scores, first / last newsletter, brand count. | Aggregate |
| get_recommendations | AI improvement recommendations across your newsletters with rationale and expected impact. | Strategy |
| get_topics | Top topics and keywords across the newsletters you track, ranked by frequency. | Insights |
Drop these into Claude, ChatGPT, or Cursor once Newsletrix is connected.
Summarize every newsletter that landed in my Newsletrix account this week. Group by brand, flag anything with a strong promo or unusual send time.
Compare Acme and Vega over the last 30 days. Where is each one stronger - subject lines, CTAs, cadence? Give me a single paragraph I can share with the team.
Which topics show up in less than 10% of competitor sends but get the highest estimated open rates? Sort by topic, return five.
Show me the three highest-scoring subject lines across every brand I track this quarter. For each one, explain why it likely worked.
Pull the top recommendations from Newsletrix and turn them into a checklist I can hand to a junior copywriter. Order by expected business impact.
Open the analysis for newsletter UUID abc123. Walk me through the SWOT, then suggest two A/B tests I should run on next week's send.
Generate a token, paste a config, ask a question. That's the whole setup.
Open Settings → AI assistant (MCP) in your Newsletrix dashboard. Click "New token", name it per device, pick an expiry, copy the value.
Paste the snippet for Claude Desktop, ChatGPT connectors, or Cursor below. The endpoint is https://beacon.newsletrix.com/mcp.
The assistant auto-discovers the tools and calls them when relevant. No special syntax, no chained commands - you just ask.
One block per client. Replace YOUR_TOKEN with the value from your dashboard.
Edit claude_desktop_config.json and add Newsletrix under mcpServers:
{
"mcpServers": {
"newsletrix": {
"type": "http",
"url": "https://beacon.newsletrix.com/mcp",
"headers": {
"Authorization": "Bearer YOUR_TOKEN"
}
}
}
}Restart Claude Desktop. Newsletrix tools appear in the connectors menu.
In ChatGPT settings, open Connectors → Add custom connector and use these values:
Name: Newsletrix
URL: https://beacon.newsletrix.com/mcp
Authentication: Bearer
Token: YOUR_TOKENSave and enable. ChatGPT will call Newsletrix tools whenever your prompt looks like newsletter analytics work.
Open Settings → MCP in Cursor and paste:
{
"mcpServers": {
"newsletrix": {
"url": "https://beacon.newsletrix.com/mcp",
"headers": {
"Authorization": "Bearer YOUR_TOKEN"
}
}
}
}Cursor will list list_newsletters, get_newsletter, and the rest in the tools panel.
What changes when your assistant can actually read your Newsletrix account.
| You ask | Without MCP | With Newsletrix MCP |
|---|---|---|
| "What did my competitors send last week?" | Generic guess based on training data | Pulls real sends from your account, by brand and date |
| "Compare Acme vs Vega on subject lines" | Hand-roll a CSV first | Uses live aggregate metrics per brand |
| "Top 5 recommendations to ship this week" | Best-practice fluff | Pulls your actual ranked recommendations |
| "Show me the analysis for newsletter X" | "I don't have access to that" | Returns the SWOT, scores, and rationale |
| End-to-end answer time | Re-prompt & copy-paste | One question |
The short version of everything teams ask before flipping it on.
Model Context Protocol - an open standard that lets AI assistants connect to external tools and data sources in a structured, auditable way. Newsletrix runs an MCP server so any compatible client can read your analytics.
Claude Desktop, ChatGPT (Pro / Team / Enterprise), Cursor, Zed, and any other MCP-compatible client. Both modern Streamable HTTP and legacy SSE transports are supported.
Yes. Like every Newsletrix feature, the MCP server is included on every plan, including the free tier.
Bearer-token auth, scoped to your account. You generate, name, and revoke tokens from your dashboard. Tokens never see another user's data.
No. The exposed tools are read-only. Your assistant can list, fetch, and search - it can't delete newsletters, edit recommendations, or change settings.
Anything that speaks MCP can connect. Local LLM frontends like Cursor's local mode, custom Claude SDK agents, and self-hosted clients all work the same way.
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