FinanceExpert
mcp-stock-server (FinanceExpert)
Ein kleiner Model Context Protocol-Server, der mit FastMCP erstellt wurde. Er stellt Marktdaten von Yahoo Finance bereit (via yfinance), sodass Assistenten Kurse, Historien als CSV und Unicode-Preischarts im Klartext abrufen können.
Anforderungen
Python 3.11+
uv (empfohlen) oder eine andere Methode zur Installation der Abhängigkeiten aus der
pyproject.toml
Related MCP server: Yahoo Finance MCP Server
Einrichtung
cd mcp-stock-server
uv syncAusführung (stdio)
Der Server spricht MCP über stdio (der Standard für mcp.run()):
uv run python server.pyAls MCP-Server hinzufügen (Cursor)
Öffnen Sie Cursor Settings → MCP (oder bearbeiten Sie Ihre MCP-JSON-Konfiguration — oft
~/.cursor/mcp.jsonunter macOS/Linux).Registrieren Sie einen stdio-Server, dessen Arbeitsverzeichnis dieses Repository ist und dessen Befehl
server.pystartet.
Option A — uv run (empfohlen)
Ersetzen Sie /absolute/path/to/mcp-stock-server durch den tatsächlichen Pfad, unter dem Sie das Repository geklont haben.
{
"mcpServers": {
"FinanceExpert": {
"command": "uv",
"args": ["run", "python", "server.py"],
"cwd": "/absolute/path/to/mcp-stock-server"
}
}
}Nach uv sync verwendet dies die fixierten Abhängigkeiten aus der uv.lock.
Option B — Projekt-Virtualenv Python
Verwenden Sie dies, wenn Sie uv nicht vom MCP-Client aus aufrufen möchten:
{
"mcpServers": {
"FinanceExpert": {
"command": "/absolute/path/to/mcp-stock-server/.venv/bin/python",
"args": ["server.py"],
"cwd": "/absolute/path/to/mcp-stock-server"
}
}
}Erstellen Sie zuerst das venv (vom Repository-Stammverzeichnis aus): uv sync (installiert Abhängigkeiten in .venv).
Speichern Sie die Konfiguration und starten Sie Cursor neu (oder laden Sie MCP neu). Im MCP-Panel sollten Sie FinanceExpert mit den Tools
get_stock_analysis,get_historical_pricesundget_stock_price_chartsehen.
Andere MCP-Clients (z. B. Claude Code, Editoren mit MCP-Unterstützung) verwenden dasselbe Prinzip: command + args + cwd für einen stdio-Server.
Tools
Tool | Beschreibung |
| Snapshot-Text: aktueller Preis, 50-Tage-Durchschnitt, Analysten-Empfehlungsschlüssel (aus |
| Tägliche Schlusskurs-Spalte als CSV für einen Rückblick von |
| Gezeichnetes ASCII/Unicode-Diagramm: Flächenfüllung, Preisachse, Start-/Enddaten auf der Zeitachse und ein 8-stufiger Sparkline-Chart. |
get_stock_price_chart Parameter
ticker— Symbol, z. B.INTU,AAPL.days— Wird verwendet, wennperiodweggelassen wird: Yahoo-BereichNd(Kalendertage). Standard 30.period— Optionaler Yahoo-Zeitraum-String; wenn gesetzt, überschreibt erdays. Beispiele:10y,5y,1y,6mo,ytd,max.
Beispiele:
Letzter Monat der Handelssitzungen (nach Kalendertagen):
days=30Letzte zehn Kalenderjahre (Yahoo-Fenster):
period="10y"
Marktdaten stammen von Yahoo über yfinance; die Semantik entspricht yfinance history(period=...).
Haftungsausschluss
Kurse und Historien dienen nur zu Informationszwecken und stellen keine Anlageberatung dar. Yahoo-Daten können verzögert sein oder Fehler enthalten; überprüfen Sie diese für Entscheidungen unabhängig.
Available Tools
3 toolsget_historical_pricesC
Fetches historical closing prices for chart generation.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | ||
| days | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | ||
| days | No | ||
| period | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
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.
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.
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.
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.
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.
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.
3 tool updates
v0.1.0- First observed
get_historical_prices - First observed
get_stock_analysis - First observed
get_stock_price_chart
TDQS
Scored across 3 tools
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.
All tools use a consistent get_verb_noun pattern (get_historical_prices, get_stock_analysis, get_stock_price_chart). Naming is clear and predictable.
With 3 tools covering historical data, real-time analysis, and charting, the set is appropriately scoped for a finance assistant. No tool feels unnecessary.
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
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