Daito

Daito

MCP server for screening Indian stocks and mutual funds by wrapping screener.in and Morningstar India, enabling fundamental queries from Claude or Cursor.

Category
访问服务器

README

Daito

MCP server for screening Indian stocks and mutual funds. Wraps screener.in and Morningstar India so you can run fundamental queries straight from Claude or Cursor.

Deployed as a Next.js app on Vercel. The MCP endpoint is at /api/mcp.

Tools

query_india_screener

Runs screener.in's query language against NSE/BSE-listed equities. Same syntax you'd use on the website:

Market Capitalization > 500 AND Price to earning < 15 AND Return on capital employed > 22

Supports 100+ fundamental ratios including annual, quarterly, and multi-year growth variants. Screener.in caps queries at 1500 characters (~40 conditions).

Requires a screener.in account. Ad-hoc queries are login-gated on their end, so you'll need to set SCREENER_IN_EMAIL and SCREENER_IN_PASSWORD. Free account at screener.in/register.

get_india_fund_screener

Screens ~12,700 India-domiciled open-end fund share classes via Morningstar India's API. No credentials needed.

Filters: category (55 Morningstar India categories), star rating, risk rating, expense ratio, AUM, yield, manager tenure, trailing returns (1D to 10Y). Each fund shows up once per share class (Direct/Regular × Growth/IDCW); use term: "Dir Gr" to narrow to direct growth plans. Values in INR, NAVs update daily.

Setup

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "daito": {
      "url": "https://your-deployment.vercel.app/api/mcp"
    }
  }
}

Restart Claude Desktop. For local dev, swap in http://localhost:3000/api/mcp.

Cursor

Add to ~/.cursor/mcp.json (global) or .cursor/mcp.json in your project:

{
  "mcpServers": {
    "daito": {
      "url": "https://your-deployment.vercel.app/api/mcp"
    }
  }
}

Restart Cursor. For local dev, use http://localhost:3000/api/mcp.

Running locally

bun install
cp .env.example .env   # fill in screener.in credentials
bun run dev

Other commands:

bun run build      # production build
bun run start      # serve production build
bun run typecheck  # tsc --noEmit

Environment variables

SCREENER_IN_EMAIL and SCREENER_IN_PASSWORD are only needed for query_india_screener. The fund screener works without credentials.

How it works

app/api/[transport]/route.ts  (mcp-handler, Zod validation)
    ↓
lib/services/
    ├── screener-in.ts          → Django CSRF login → /screen/raw/ → cheerio HTML parse
    └── india-fund-screener.ts  → public Morningstar JWT → ecint/v1/screener (FOIND$$ALL)

The screener.in service does a Django CSRF login, caches the session cookie, and re-auths when it expires. The Morningstar service scrapes a public retail JWT from their quickrank page and refreshes it from the JWT exp claim.

Deployment

Hosted on Vercel. vercel.json bumps maxDuration to 60s on the transport route since screener.in can be slow. Node runtime.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选