Semantic BI MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Semantic BI MCPWhat's our monthly recurring revenue?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Semantic BI MCP
Model Context Protocol (MCP) server that gives AI assistants a safe, correct data-analyst capability over business metrics - without raw SQL improvisation.
Talk to your data in plain English. Get answers that are always correct and can never break anything.
What makes this different
Most data MCPs expose a raw SQL runner and let the model improvise. That miscounts, mis-joins, ignores soft-deletes, and can mutate or leak data.
This project does the opposite: a semantic layer. Every business metric is defined once as vetted SQL in lib/metrics.ts and exposed as an MCP tool. The model assembles answers from correct building blocks. Guardrails (read-only, caps, PII masking, audit log) are first-class features.
Related MCP server: @pilat/mcp-datalink
Architecture
One Next.js app, four layers:
Layer | Path | Purpose |
MCP server |
| Tools, resources, prompts at |
Semantic layer |
| sql.js dataset, metrics, guards, audit, auth |
LangChain agent |
|
|
Chat UI |
| Live tool-call visualization |
Tech stack
Next.js 15 (App Router), TypeScript, Tailwind CSS 4
MCP:
mcp-handler+@modelcontextprotocol/sdk@^1.26Data:
sql.js(WASM SQLite, serverless-safe)Agent:
@langchain/mcp-adapters,@langchain/langgraph,@langchain/openaiDeploy: Vercel Pro + Fluid compute
Quick start
See INSTALLATION.md for full setup including environment variables.
npm install
cp .env.example .env.local # fill in keys
npm run devChat UI: http://localhost:3000
MCP endpoint: http://localhost:3000/api/mcp
MCP Inspector:
npx @modelcontextprotocol/inspector
MCP capabilities
Tools (11)
Tool | Description |
| Monthly Recurring Revenue |
| Annual Recurring Revenue |
| Subscription churn % |
| Active/trialing count by tier |
| New customer acquisitions |
| Paid revenue by plan |
| Active customer count |
| NRR between two months |
| Read-only SELECT on whitelisted views |
| Metric catalog |
| Recent tool invocations |
Resources (3)
dataset://schema- table/view definitionssemantic-layer://catalog- metric catalog JSONdataset://stats- dataset overview
Prompts (3)
executive-summary- monthly SaaS health summarymrr-trend-analysis- compare two monthschurn-investigation- structured churn analysis
Security
See SECURITY.md for the full security audit and status.
Project docs
INSTALLATION.md - setup and env var guide
SECURITY.md - security posture and audit
License
Neural LB - portfolio / demo use. Dataset is fictional (Northwind SaaS).
This server cannot be deployed
Maintenance
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