mcp_massive MCP — Casos de uso, Instalar & Demo en vivo

Por qué usarlo

Características clave

Dynamic endpoint discovery — no hardcoded tool list for 100+ API endpoints
DataFrame storage with in-memory SQL — chain calls without token explosion
Built-in: Black-Scholes, return calcs, technical indicators
Covers stocks, options, forex, crypto, futures, real-time trades, fundamentals
Install via uv tool install; Python 3.12+

Demo en vivo

Cómo se ve en la práctica

massive.replay ▶ listo

0/0

Instalar

Elige tu cliente

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "massive": {
      "command": "uvx",
      "args": [
        "mcp_massive"
      ],
      "_inferred": true
    }
  }
}

Abre Claude Desktop → Settings → Developer → Edit Config. Reinicia después de guardar.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "massive": {
      "command": "uvx",
      "args": [
        "mcp_massive"
      ],
      "_inferred": true
    }
  }
}

Cursor usa el mismo esquema mcpServers que Claude Desktop. La configuración del proyecto prevalece sobre la global.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "massive": {
      "command": "uvx",
      "args": [
        "mcp_massive"
      ],
      "_inferred": true
    }
  }
}

Haz clic en el icono MCP Servers de la barra lateral de Cline y luego en "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "massive": {
      "command": "uvx",
      "args": [
        "mcp_massive"
      ],
      "_inferred": true
    }
  }
}

Mismo formato que Claude Desktop. Reinicia Windsurf para aplicar.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "massive",
      "command": "uvx",
      "args": [
        "mcp_massive"
      ]
    }
  ]
}

Continue usa un array de objetos de servidor en lugar de un mapa.

~/.config/zed/settings.json

{
  "context_servers": {
    "massive": {
      "command": {
        "path": "uvx",
        "args": [
          "mcp_massive"
        ]
      }
    }
  }
}

Añádelo a context_servers. Zed recarga en caliente al guardar.

claude mcp add massive -- uvx mcp_massive

Un solo comando. Verifica con claude mcp list. Quita con claude mcp remove.

Casos de uso

Usos del mundo real: mcp_massive

Analyze an options chain and price theoretical value

👤 Options traders, quant hobbyists ⏱ ~20 min advanced

Cuándo usarlo: You want to look at AAPL options, compare IV to historical vol, and spot-check Black-Scholes values.

Requisitos previos

Massive.com API key — massive.com signup — free tier

Flujo

Find the right endpoint

Search endpoints: 'options chain for a given ticker and expiry'.✓ Copiado

→ Best-match endpoint + params
Pull chain

Call the endpoint for AAPL with the next monthly expiry. Store as DataFrame 'aapl_chain'.✓ Copiado

→ DataFrame stored; head preview
Analyze

Run SQL: SELECT strike, iv, bid, ask FROM aapl_chain WHERE expiry=... ORDER BY strike. Price Black-Scholes for each and show deltas to market mid.✓ Copiado

→ Table of strikes with BS-vs-market

Resultado: Hands-on options screen without writing Python yourself.

Errores comunes

Delayed data on free tier — Check data timestamps; paid tier for real-time

Compute total return for a portfolio over a period

👤 Investors tracking performance ⏱ ~15 min intermediate

Cuándo usarlo: Year-end — how did my 10-position portfolio perform vs SPY?

Flujo

Fetch prices

For each ticker in [list], get daily close prices from Jan 1 to today. Store each as a DataFrame.✓ Copiado

→ Price series per ticker
Compute weighted return

Using my weights [paste], compute weighted portfolio return. Compare to SPY return over the same period.✓ Copiado

→ Portfolio YTD vs SPY YTD

Resultado: Quick portfolio report without spreadsheets.

Errores comunes

No dividend reinvestment accounting by default — Use adjusted-close series; ask Claude to note the assumption

Combinar con: filesystem

Screen stocks on fundamental criteria

👤 Value investors ⏱ ~20 min intermediate

Cuándo usarlo: You want US large-cap stocks with P/E < 15, dividend yield > 3%, and positive 5y earnings growth.

Flujo

Find endpoints

Search endpoints for 'fundamentals' and 'screener'. Pick the right one.✓ Copiado

→ Endpoint choice
Screen

Pull fundamentals for S&P 500 components. Store as DataFrame. Run SQL to filter my criteria.✓ Copiado

→ Matching tickers with key ratios

Resultado: A shortlist to research further.

Errores comunes

Fundamentals data lags quarterly filings by weeks — Check as_of dates

Combinaciones

Combínalo con otros MCPs para multiplicar por 10

massive + filesystem

Persist analysis to CSV for Excel follow-up

After the screen, export the final DataFrame as /reports/screen-YYYY-MM-DD.csv.✓ Copiado

Herramientas

Lo que expone este MCP

Herramienta	Entradas	Cuándo llamar	Coste
search_endpoints	query: str	First step — discover what's available	free
get_endpoint_docs	endpoint_id	Before calling an endpoint you don't know	free
call_api	endpoint, params, store_as?: str	Actually fetch data; store to re-query	1 API call
query_data	sql: str	Analyze stored DataFrames without re-fetching	free

Coste y límites

Lo que cuesta ejecutarlo

Cuota de API: Per Massive.com plan
Tokens por llamada: Raw series can be large — use DataFrame + SQL to slice
Monetario: Free tier exists; paid for real-time / higher volume
Consejo: store_as + query_data is dramatically cheaper than re-fetching and re-parsing each time.

Seguridad

Permisos, secretos, alcance

Almacenamiento de credenciales: MASSIVE_API_KEY env var

Salida de datos: Queries to massive.com

Project is marked experimental; breaking API changes possible. Pin version.
Financial data is for info only — this is not investment advice and the LLM can miscompute.

Resolución de problemas

Errores comunes y soluciones

401 from Massive

Check API key. Verify it's still active in the dashboard.

DataFrame limit exceeded (50 / 50k rows default)

Raise via env config or chunk via SQL limits.

SQL syntax error in query_data

Query engine is a subset — check docs for supported functions.

Alternativas

mcp_massive vs otros

Alternativa	Cuándo usarla	Contrapartida
Alpaca MCP	You want trading too, not just data	Different broker; narrower data
Polygon.io / Alpha Vantage direct + fetch MCP	You want full API control	You write the fetching and parsing yourself

Más

Recursos

📖 Lee el README oficial en GitHub

🐙 Ver issues abiertas

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