MCP server

Shibui Finance Official

finance.shibui/data

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

9,900+ US equities, 64 years of prices, financials, technicals, and earnings. Ask in plain English.

Working at last checkVerified publisher: shibui.financeAbout 2,330 tokens per request once connected12 tools

https://mcp.shibui.finance/mcp

At a glance

Type: MCP server
Publisher: shibui.finance (verified by the MCP Registry)
Status: Working at last check
Tools: 12
Token cost: About 2,330 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http data https://mcp.shibui.finance/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.data]
url = "https://mcp.shibui.finance/mcp"

Gemini CLI

{"mcpServers":{"data":{"httpUrl":"https://mcp.shibui.finance/mcp"}}}

Cursor

{"mcpServers":{"data":{"url":"https://mcp.shibui.finance/mcp"}}}

VS Code

{"servers":{"data":{"type":"http","url":"https://mcp.shibui.finance/mcp"}}}

Antigravity

agy mcp add data https://mcp.shibui.finance/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"data","server_url":"https://mcp.shibui.finance/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"data","server_url":"https://mcp.shibui.finance/mcp"}

Tools

export_to_excel ~185 tokens
Export query results to a branded Shibui Finance Excel spreadsheet. Runs the same SQL query as stock_data_query but returns a downloadable Excel file instead of raw data. The spreadsheet includes branded headers, smart number formatting, and auto-fitted columns.
get_database_schema ~256 tokens
REQUIRED for US stock/financial queries, authoritative source, call FIRST Use this tool when the user asks about stock prices, revenue, earnings, earnings surprises (EPS estimates vs actuals), margins, P/E ratios, valuations, dividends, balance sheets, cash flow, technical indicators (RSI, MACD, SM
get_query_patterns ~165 tokens
REQUIRED before stock_data_query, 23 SQL patterns prevent timeouts/wrong results Must be called once per session immediately after get_database_schema. Contains query patterns for time-series selection, return calculations, screening joins, window functions, backtesting, and performance optimizatio
load_backtesting_workflow ~203 tokens
Load backtesting workflow for stop-loss, exit rules, Sharpe, forward returns. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to backtest, simulate, validate a strategy, test "what happens after X", compare forward r
load_comparison_workflow ~148 tokens
Load comparison workflow for X vs Y, peer analysis, relative valuation. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to compare companies, "X vs Y", "how does X compare to Y", peer benchmarking, sector peers, side
load_earnings_workflow ~156 tokens
Load earnings workflow for EPS surprises, beat/miss, estimates, revenue. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about earnings results, EPS surprises, beat/miss history, "did X beat estimates", quarterly ear
load_filing_workflow ~210 tokens
Load filing workflow for SEC/EDGAR metadata, 8-K events, 10-K/10-Q reports. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL whenever the user asks about filing dates, filing activity, "who filed", "filed a form", filing frequency, SEC
load_fundamental_workflow ~157 tokens
Load fundamental workflow for valuation, cash flow, margins, balance sheet. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about company valuation, "is X a good buy", financial health, debt levels, profitability rat
load_insider_workflow ~191 tokens
Load insider workflow for Form 3/4/5, insider buy/sell, cluster buy, 13D/G. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about insider transactions, insider buying/selling, Form 3 initial holdings, Form 4/5 transa
load_screening_workflow ~161 tokens
Load screening workflow to find, filter, scan, rank stocks, top N by.... REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks to find, screen, scan, rank, or filter stocks — "find stocks that...", "top 10 by...", "best di
load_technical_workflow ~163 tokens
Load technical workflow for RSI, MACD, SMA, Bollinger Bands, entry/exit. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about RSI, MACD, moving averages, Bollinger Bands, support/resistance, overbought/oversold, mom
stock_data_query ~335 tokens
Stock prices, earnings, revenue, P/E, dividends, filings, screener, comparisons Run a SQL query against 64 years of US stock market data. REQUIRES calling get_database_schema then get_query_patterns first (in that order). This tool has no schema or query patterns built in. Call get_database_schem

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