Click on "Install 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., "@quantdb-mcp What are the latest stock prices and company names?"
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.
量化金融数据库 + 只读 SQL MCP 服务。
数据源：easy-tdx（通达信 TCP 行情）+ pywestockdata（腾讯/东财基本面 HTTP）
存储：DuckDB 双文件 —— quantdb_ods.duckdb（ODS 原始层）/ quantdb.duckdb（DWD 层，清洗后）
接口：FastMCP streamable-http 只读 query(sql) 工具（可跨库 JOIN）
层 | 库文件 | 表 |
ODS | quantdb_ods.duckdb | stock_basic / daily_kline / realtime_quote / finance_income / finance_balance / finance_cashflow |
DWD | quantdb.duckdb | dim_stock（去重标准化）/ fact_daily（列名统一） |
APP | - | 后续因子层（可复用 factor-pipeline 表达式引擎） |
ODS 可整体重灌，DWD 由 sync_dwd 全量重建（幂等）。
Related MCP server: A股实时行情MCP服务器
cd projects/quantdb-mcp
uv sync # 或 pip install -e .依赖：duckdb、fastmcp、pywestockdata、easy-tdx、click。
quantdb init # 建库建表（双文件）
quantdb full-load # 全量同步：代码表 → 日K → 财务 → DWD 重建
quantdb full-load --codes 50 --kline-count 120 # 限前 50 只、每只 120 根K线（试跑用）
quantdb update --once # 增量同步 + 一次实时快照
quantdb update # 盘中 30s 快照循环（Ctrl+C 退出）
quantdb summary # 各表行数与最新日期数据目录通过环境变量 QUANTDB_DATA_DIR 指定（默认 ./data）。
启动服务（streamable-http）：
uv run python -m quantdb.server.mcp # 等价 pip 安装后的 quantdb-mcp注册到 MCP 客户端（如 nanobot / Claude Desktop）：
{
"mcpServers": {
"quantdb": {
"command": "quantdb-mcp",
"type": "stdio"
}
}
}查询示例（query 工具，只读）：
SELECT * FROM dim_stock WHERE market = 'sh' LIMIT 5
SELECT d.code, s.name, d.close FROM fact_daily d JOIN ods.stock_basic s ON d.code = s.code
WHERE d.date = (SELECT max(date) FROM fact_daily)仅允许单条 SELECT / WITH；写语句、多语句被拒绝
表白名单：仅业务表（ODS 用 ods. 前缀），内部表不可见
最多返回 10_000 行；查询超时 30s；DuckDB 以只读模式打开
uv run pytest # 97 tests，100% 覆盖率（mock 数据源，不依赖网络）
uv run ruff check src tests # 0 error详见 design.md 与 task_list.md。
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
The stock market, in SQL — scan, replay, or subscribe across ~12k US tickers and top 100 cryptos.
Read-only China A-share data for AI agents: market, limit-up, capital flow and disclosures.
7-factor stock scoring MCP server. US/HK/CN, 74 stocks. Free + Premium (USDC/Base). x402 ready.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/openbot-coder/quantdb-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server