Marketing Intelligence & Optimization
ai.saifsPublished by saifs.aiOfficial publisherv1.0.1Updated Oct 24, 2026
Analyze Product performance on Platforms like youtube, instagram etc. To optimize Marketing.
The publisher's own server: Customer Intelligence & Segmentation
Overview
Remote MCP server that turns ad spend, sales, basket and A/B test data into ranked marketing decisions with money impact and confidence.
- What you can do
- Analyze marketing data: submit spend, sales, baskets, A/B tests, adoption and customer revenue arrays (up to 200 rows each) and get ranked STOP/SCALE/SHIP/WAIT decisions.
- Review channel economics: channel ROI, saturation, budget reallocation, and CAC, LTV and payback by channel.
- Evaluate experiments and products: A/B significance with power and peeking checks, market-basket bundles, and Bass diffusion for new-product ramps.
- Generate a local script: get a numpy-only Python script that runs the same analysis on larger exports so the data stays off the server.
- When to use it
- Useful when you want an assistant to interpret marketing performance data and recommend where to scale, cut or wait, or to sanity-check whether an A/B test result is real. Also suited to bundling and unit-economics questions when you can supply the underlying tables.
- Requirements
- A remote Streamable HTTP endpoint; nothing to install. OAuth 2.1 sign-in with PKCE and dynamic client registration, so the client opens a sign-in page on first use. An OAuth-aware MCP client is needed; the server answers unauthenticated requests with a 401 challenge.
Installation
In SourceWeft
- Open Marketing Intelligence & Optimization in the dashboard and add it to a workspace.
- Connect the required credentials. They are stored privately and never shown on public pages.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Use with an agent
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/ai.saifs%2Fmarketing-intelligence/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Other MCP clients
Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.
{
"mcpServers": {
"marketing-intelligence-optimization": {
"type": "http",
"url": "https://marketing-analysis-mcp.saifs.ai/mcp"
}
}
}README
Marketing Intelligence & Optimization
Turns ad spend, sales, order baskets, A/B test counts and adoption data into ranked STOP / SCALE / SHIP / WAIT decisions with money impact and confidence. Covers marketing mix modelling (channel ROI, saturation and budget reallocation), market-basket bundles, A/B significance with power and peeking checks, Bass diffusion for new-product ramps, and CAC / LTV / payback by channel. Each part runs only when its data is supplied; MMM results are directional, not causal.
Install
VS Code / GitHub Copilot
Add to .vscode/mcp.json (workspace) or your user mcp.json:
Then start the server from the MCP view and sign in when prompted.
Claude (claude.ai, Desktop)
Settings → Connectors → Add custom connector, and paste:
Claude Code
Any other MCP client
Point it at https://marketing-analysis-mcp.saifs.ai/mcp using the Streamable HTTP transport. The server returns 401 with a
WWW-Authenticate: Bearer … resource_metadata=… challenge, so OAuth-aware clients sign in automatically.
Tools
Example prompts
- “Here's our weekly Meta, Google and email spend with sales. Which channel should we scale or cut?”
- “Is our landing-page A/B test win real, or is it under-powered?”
- “Which products should we bundle, based on these order baskets?”
Support
- Website: https://saifs.ai
- Issues: https://github.com/Saify-Technologies/saifs-ai-mcps-docs/issues
- Privacy: https://saifs.ai/privacy_policy
Source: servers/marketing-intelligence/README.md at commit 2b4eab8
Tools
0Version history
2- v1.0.1LatestOct 21, 2026
- v1.0.0Sep 16, 2026
Score
85% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 daysRequired25 pts
- Auth declaredRequired10 pts
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
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