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geddamsatish

FinanceExpert

by geddamsatish

mcp-stock-server (FinanceExpert)

Un pequeño servidor Model Context Protocol construido con FastMCP. Expone datos de mercado de Yahoo Finance (a través de yfinance) para que los asistentes puedan obtener cotizaciones, historial en formato CSV y gráficos de precios en texto plano Unicode.

Requisitos

  • Python 3.11+

  • uv (recomendado) u otra forma de instalar dependencias desde pyproject.toml

Related MCP server: Yahoo Finance MCP Server

Configuración

cd mcp-stock-server
uv sync

Ejecución (stdio)

El servidor utiliza MCP a través de stdio (el valor predeterminado para mcp.run()):

uv run python server.py

Añadir como servidor MCP (Cursor)

  1. Abre Cursor Settings → MCP (o edita tu configuración JSON de MCP, a menudo ~/.cursor/mcp.json en macOS/Linux).

  2. Registra un servidor stdio cuyo directorio de trabajo sea este repositorio y cuyo comando inicie server.py.

Opción A — uv run (recomendado)

Reemplaza /absolute/path/to/mcp-stock-server con la ruta real donde clonaste el repositorio.

{
  "mcpServers": {
    "FinanceExpert": {
      "command": "uv",
      "args": ["run", "python", "server.py"],
      "cwd": "/absolute/path/to/mcp-stock-server"
    }
  }
}

Después de uv sync, esto utiliza las dependencias bloqueadas de uv.lock.

Opción B — Python en entorno virtual del proyecto

Utiliza esto si prefieres no invocar uv desde el cliente MCP:

{
  "mcpServers": {
    "FinanceExpert": {
      "command": "/absolute/path/to/mcp-stock-server/.venv/bin/python",
      "args": ["server.py"],
      "cwd": "/absolute/path/to/mcp-stock-server"
    }
  }
}

Crea el venv primero (desde la raíz del repositorio): uv sync (instala las dependencias en .venv).

  1. Guarda la configuración y reinicia Cursor (o recarga MCP). En el panel de MCP deberías ver FinanceExpert con las herramientas get_stock_analysis, get_historical_prices y get_stock_price_chart.

Otros clientes MCP (por ejemplo, Claude Code, editores con soporte MCP) utilizan la misma idea: command + args + cwd para un servidor stdio.

Herramientas

Herramienta

Descripción

get_stock_analysis

Texto instantáneo: precio actual, promedio de 50 días, clave de recomendación de analistas (desde Ticker.info).

get_historical_prices

Columna de cierre diario como CSV para un periodo de days días naturales (period=f"{days}d"). Por defecto days=30.

get_stock_price_chart

Gráfico ASCII/Unicode dibujado con cajas: relleno de área, eje de precios, fechas de inicio/fin en el eje temporal y un sparkline de 8 pasos.

Parámetros de get_stock_price_chart

  • ticker — Símbolo, ej. INTU, AAPL.

  • days — Se utiliza cuando se omite period: rango de Yahoo Nd (días naturales). Por defecto 30.

  • period — Cadena de periodo opcional de Yahoo; cuando se establece, anula a days. Ejemplos: 10y, 5y, 1y, 6mo, ytd, max.

Ejemplos:

  • Último mes de sesiones (por días naturales): days=30

  • Últimos diez años naturales (ventana de Yahoo): period="10y"

Los datos de mercado provienen de Yahoo a través de yfinance; la semántica coincide con yfinance history(period=...).

Las cotizaciones y el historial son solo informativos, no constituyen asesoramiento de inversión. Los datos de Yahoo pueden tener retrasos o contener errores; verifica de forma independiente antes de tomar decisiones.

Available Tools

3 tools
get_historical_pricesC

Fetches historical closing prices for chart generation.

ParametersJSON Schema
NameRequiredDescriptionDefault
tickerYes
daysNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so description must disclose behavioral traits. It does not mention whether data is cached, any limits on 'days' parameter, or output format beyond 'closing prices'. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is one concise sentence, front-loaded with purpose. No fluff, but could be longer for completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an output schema exists, return values are covered. However, no guidance on parameter ranges or timezone for days, and no usage context for how this relates to chart generation. Incomplete for a tool with zero annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description should compensate. It adds no detail about 'ticker' or 'days' beyond their names. Baseline is 3 due to absence of param info in description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches historical closing prices for chart generation, specifying the action (fetch), resource (historical prices), and purpose (chart generation). However, it does not differentiate from sibling tools like get_stock_price_chart or get_stock_analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus siblings. It does not mention prerequisites, alternatives, or contexts where this tool is preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_stock_analysisA

Fetches real-time stock price, 50-day average, and analyst recommendations.

ParametersJSON Schema
NameRequiredDescriptionDefault
tickerYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It indicates the tool fetches data (non-destructive), but does not disclose any potential latency, rate limits, or data freshness. The output schema exists but is not referenced; description could hint at what fields are returned beyond what's in schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at one sentence, front-loading the key output fields. Every phrase adds value, with no waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one simple parameter and an output schema, the description could be more complete by adding a note about the ticker format or data source. It is adequate but lacks some contextual details like time zone or data provider.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (no description for the parameter), so the description must compensate. It does not explain what the ticker parameter expects (e.g., format, examples). However, the parameter has no enums and is simple, so the gap is small. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches real-time stock price, 50-day average, and analyst recommendations. The verb 'fetches' and the specific resources are well-defined, but it does not distinguish itself from sibling tools like get_historical_prices or get_stock_price_chart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for obtaining current price, average, and recommendations, but provides no explicit guidance on when to use this tool versus alternatives. For instance, it does not mention that get_historical_prices might be for historical data or get_stock_price_chart for chart data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_stock_price_chartA

Plain-text Unicode chart. Pass period (e.g. 10y, 5y, 1y) for calendar ranges, or use days alone.

ParametersJSON Schema
NameRequiredDescriptionDefault
tickerYes
daysNo
periodNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses the output format (plain-text Unicode chart) and the two ways to specify time range, but does not mention rate limits, data latency, or whether it requires authentication. The behavior is partially transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, no waste. It front-loads the key purpose and follows with parameter guidance. Efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema, the description does not need to detail return structure. It covers the main purpose, parameter usage, and output format. For a simple chart tool with 3 parameters, this is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains 'period' and 'days' parameters by specifying their relationship (period for calendar ranges, days alone). However, it does not describe the 'ticker' parameter or the exact format of 'period'. This adds some meaning but not comprehensive.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies a verb-resource-action: it creates a plain-text Unicode chart for a stock. It is distinct from 'get_historical_prices' and 'get_stock_analysis' as it focuses on chart output, though it does not explicitly differentiate from those siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear guidance on how to specify the time range: use period for calendar ranges or days alone. However, it does not explain when to prefer this tool over its siblings (e.g., when you need a visual chart vs. raw prices or analysis).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 3 tool updatesv0.1.0
    • First observedget_historical_prices
    • First observedget_stock_analysis
    • First observedget_stock_price_chart

TDQS

A3.5/5.0

Scored across 3 tools

Disambiguation4/5

Tools are mostly distinct: get_historical_prices provides raw data for charts, get_stock_analysis gives real-time price and fundamentals, and get_stock_price_chart returns a visual chart. However, get_historical_prices and get_stock_price_chart both relate to historical data, causing slight overlap.

Naming Consistency5/5

All tools use a consistent get_verb_noun pattern (get_historical_prices, get_stock_analysis, get_stock_price_chart). Naming is clear and predictable.

Tool Count5/5

With 3 tools covering historical data, real-time analysis, and charting, the set is appropriately scoped for a finance assistant. No tool feels unnecessary.

Completeness3/5

The tools cover basic stock data retrieval and charting but lack fundamental operations like search, comparison, or portfolio management. Gaps exist for a fully comprehensive finance tool.

Maintenance

ActivityInactive
ResponsivenessNo issues

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