Analytics Server
БесплатноНе проверенEnables LLMs to interact with a SQLite e-commerce database via safe, typed MCP tools with read-only guards and auth-gated mutations, plus a Claude agent for ans
Описание
Enables LLMs to interact with a SQLite e-commerce database via safe, typed MCP tools with read-only guards and auth-gated mutations, plus a Claude agent for answering business questions.
README
An MCP server that exposes a SQLite e-commerce database to any MCP client (Claude Desktop, Cursor, the Anthropic SDK, …) as safe, structured, schema-typed tools — plus a Claude agent that answers business questions by calling those tools. Built on the standard
mcpPython SDK (FastMCP). Includes a read-only SQL guard, an auth-gated mutation, and a schema resource.
MCP is the 2026 standard for connecting agents to tools and data — 10,000+ servers already published, native in ChatGPT, Claude, Cursor, Copilot, and VS Code. This repo is a clean, production-shaped example of the thing teams keep needing: a governed gateway between an LLM and a database — not raw SQL access, but typed tools with guards and authorization.
What it exposes
| Tool | Kind | Notes |
|---|---|---|
list_tables |
read | tables in the database |
describe_table(table) |
read | columns, types, primary keys |
run_query(sql) |
read | read-only ad-hoc SELECT/WITH — single statement, mutation keywords blocked, row-capped |
top_products(limit) |
read | best-sellers by units (completed orders) |
revenue_summary() |
read | revenue + order/customer counts |
create_support_ticket(...) |
write | auth-gated — requires the write API key |
schema://database |
resource | the full SQL schema |
The split is the senior point: a bash/raw-SQL tool hands the model unbounded power; these
are dedicated, typed tools the host can validate, gate, and audit. run_query is
read-only and capped; the only mutation is behind an API key.
Two ways to drive it
PY=~/miniconda3/envs/personal/bin/python
$PY -m pip install -e ".[all]"
# 1) OFFLINE — exercise the live MCP protocol end-to-end, no API key, no LLM:
$PY -m mcp_analytics.client demo
# [mcp] connected — 6 tools: list_tables, describe_table, run_query, ...
# [mcp] revenue_summary -> {"revenue": 184293.5, "orders": 968, "customers": 188}
# [mcp] top_products(3) -> [{"name": "Product 7", "category": "Books", "units": 142}, ...]
# [mcp] blocked mutation -> tool error: only SELECT / WITH queries are allowed
# 2) AGENT — let Claude answer a question by calling the tools (needs a key):
export ANTHROPIC_API_KEY=sk-ant-...
$PY -m mcp_analytics.client ask "Which country has the most customers, and what's total revenue?"
The server itself runs over stdio (python -m mcp_analytics.server) — point Claude
Desktop / Cursor / any MCP client at that command and the tools appear.
Use it from Claude Desktop / Cursor
{
"mcpServers": {
"analytics": { "command": "python", "args": ["-m", "mcp_analytics.server"] }
}
}
Architecture
MCP client (Claude Desktop · Cursor · Anthropic SDK · this client.py)
│ JSON-RPC over stdio
▼
FastMCP server (server.py) ──tools──► list_tables · describe_table · run_query
│ top_products · revenue_summary
│ create_support_ticket (auth-gated)
│ ──resource──► schema://database
▼
db.py pure, testable query layer ──► SQLite e-commerce DB (customers · products
read-only guard · auth · seed orders · order_items · tickets)
Tool logic lives in db.py (unit-tested without the protocol); server.py is the thin
FastMCP adapter. The Claude agent (client.py) converts the server's MCP tools to Anthropic
tools via anthropic.lib.tools.mcp and runs the tool loop.
Safety & governance
- Read-only SQL guard —
run_queryaccepts only a singleSELECT/WITH, rejectsINSERT/UPDATE/DELETE/DROP/ALTER/ATTACH/PRAGMA/CREATE, blocks multi-statement injection, and caps rows. Executed on amode=roSQLite connection as defence-in-depth. - Auth-gated mutation —
create_support_ticketrequires the write API key (MCP_WRITE_API_KEY); every other tool is read-only. - Validated inputs — unknown tables/customers raise typed errors surfaced to the agent.
These guards are the security-critical surface and are covered by the test suite.
Repo layout
mcp-analytics-server/
├── src/mcp_analytics/
│ ├── db.py SQLite schema + seed + pure query layer (read-only guard, auth)
│ ├── server.py FastMCP server: tools + schema resource (stdio)
│ ├── client.py MCP client: offline protocol `demo` + Claude `ask` agent
│ └── config.py paths, write API key, model
├── tests/ db + query-guard + auth tests (key-free) — 11 cases
└── pyproject.toml · Dockerfile · Makefile · .github/workflows/ci.yml
Résumé framing
Built an MCP (Model Context Protocol) server exposing a database as governed, schema-typed tools — read-only SQL guard, auth-gated mutations, and a schema resource — on the standard
mcpSDK; plus a Claude agent that answers business questions through it. Demonstrates the 2026 agent-integration standard end-to-end (stdio transport, tool conversion, tool loop).
License
MIT (LICENSE).
Установка Analytics Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/tkarim45/mcp-analytics-serverFAQ
Analytics Server MCP бесплатный?
Да, Analytics Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Analytics Server?
Нет, Analytics Server работает без API-ключей и переменных окружения.
Analytics Server — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Analytics Server в Claude Desktop, Claude Code или Cursor?
Открой Analytics Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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