Triple Whale▌
by triple-whale
Connect Triple Whale to analyze e-commerce sales, build actionable sales dashboards, and use marketing attribution tools
Integrates with Triple Whale's API to enable querying and analysis of e-commerce performance metrics for sales reporting and marketing strategy optimization.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / E-commerce business owners tracking performance
- / Marketing managers analyzing ad spend ROI
- / Analysts creating sales reports
- / Teams monitoring profit margins
capabilities
- / Query net profit and revenue metrics
- / Analyze ad ROAS by attribution model
- / Rank countries by revenue and user acquisition
- / Check Meta advertising spend data
- / Generate sales performance reports
- / Compare metrics across time periods
what it does
Connects Claude to Triple Whale's e-commerce analytics API, letting you query sales, marketing, and profit data using natural language commands.
about
Triple Whale is an official MCP server published by triple-whale that provides AI assistants with tools and capabilities via the Model Context Protocol. Connect Triple Whale to analyze e-commerce sales, build actionable sales dashboards, and use marketing attribution tools It is categorized under finance, analytics data.
how to install
You can install Triple Whale in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Triple Whale is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Triplewhale MCP Server
Model Context Protocol (MCP) is a new, standardized protocol for managing context between large language models (LLMs) and external systems. In this repository, we provide an installer as well as an MCP Server for Triplewhale.
This lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Triplewhale, e.g.:
Was my net profit positive last month?.Rank countries by order revenue and new users for the last quarter..Give me ads ROAS over the last 7 days and break it out by attribution model?
Claude Setup
Installing via Smithery
To install Triplewhale MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install triplewhale --client claude
Requirements
- Node.js >= v18.0.0
- Claude Desktop
- Triplewhale API key - you can generate one through the Triplewhale console. Learn more or click here for quick access.
How to use locally
- Run
npx -y @triplewhale/mcp-server-triplewhale init $TRIPLEWHALE_API_KEY - Restart Claude Desktop
- You should now be able to try a simple command such as
what's my meta spend in the last 7 days?
Supported Tools
moby
Development with Claude Desktop
npm install
npm run build
npm run watch # You can keep this open.
node dist/index.js init $TRIPLEWHALE_API_KEY
Then, restart Claude each time you want to test changes.
Testing
To run the tests you need to setup the .env file according to the .env.example file.
npm run test
FAQ
- What is the Triple Whale MCP server?
- Triple Whale is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Triple Whale?
- This profile displays 56 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★56 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
Useful MCP listing: Triple Whale is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Alexander Agarwal· Dec 24, 2024
I recommend Triple Whale for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Hiroshi Garcia· Dec 24, 2024
Triple Whale is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Kaira Brown· Dec 24, 2024
Triple Whale has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Kofi Taylor· Dec 4, 2024
According to our notes, Triple Whale benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Piyush G· Nov 19, 2024
We evaluated Triple Whale against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Kiara Garcia· Nov 15, 2024
Strong directory entry: Triple Whale surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Hiroshi Flores· Nov 15, 2024
We wired Triple Whale into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Alexander Bansal· Nov 15, 2024
Triple Whale reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Nia Huang· Nov 11, 2024
Triple Whale is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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