
Market Data
jquants-mcp
jquants-mcp provides command-line access to Tokyo Stock Exchange data via the official J-Quants API. It lets users search TSE-listed stocks by code or Japanese company name, retrieve daily OHLCV time series with configurable date ranges and JSON output, fetch financial summaries (revenue, profit, EP
Overview
jquants-mcp provides command-line access to Tokyo Stock Exchange data via the official J-Quants API.
jquants-mcp provides command-line access to Tokyo Stock Exchange data via the official J-Quants API. It lets users search TSE-listed stocks by code or Japanese company name, retrieve daily OHLCV time series with configurable date ranges and JSON output, fetch financial summaries (revenue, profit, EPS, ROE), compare metrics across companies, and view an earnings announcement calendar. Typical use cases include programmatic backtesting, financial analysis, reporting, portfolio monitoring, and preparing earnings workflows. Key features: stock search, price history with date filters, financials endpoint, earnings calendar queries, connectivity test, and machine-readable JSON output for integration with data pipelines. Setup requires JQUANTS_MAIL_ADDRESS and JQUANTS_PASSWORD environment variables and pip install jquants-mcp. Note: data is for personal use only; redistribution is prohibited by J-Quants Terms of Service.
Skill.md
How this skill works
jquants-mcp provides command-line access to Tokyo Stock Exchange data via the official J-Quants API. It lets users search TSE-listed stocks by code or Japanese company name, retrieve daily OHLCV time series with configurable date ranges and JSON output, fetch financial summaries (revenue, profit, EP
J-Quants: JPX Stock Market Data
Access Tokyo Stock Exchange (TSE) listed stock data via the official J-Quants API. Search stocks, get daily OHLCV prices, financial summaries, and earnings announcement calendar.
Important: This tool is for personal use only. Data redistribution is prohibited by J-Quants Terms of Service. https://jpx-jquants.com/termsofservice
Use Cases
- Search for TSE-listed stocks by code or company name
- Get daily OHLCV price data for any stock
- Retrieve financial summaries (revenue, profit, EPS, ROE)
- Check upcoming earnings announcement dates
- Compare financial metrics across companies
Commands
Search stocks
# By stock code
jquants-mcp search 7203
# By company name (Japanese)
jquants-mcp search トヨタ
# JSON output
jquants-mcp search ソニー --json-output
Get stock prices
# Default: last 30 days
jquants-mcp price 7203
# With date range
jquants-mcp price 7203 --start-date 2024-01-01 --end-date 2024-12-31
# JSON output
jquants-mcp price 7203 --json-output
Get financial data
jquants-mcp financials 7203
jquants-mcp financials 6758 --json-output
Get earnings calendar
# Default: next 30 days
jquants-mcp calendar
# With date range
jquants-mcp calendar --start-date 2024-04-01 --end-date 2024-06-30
Test connectivity
jquants-mcp test
Workflow
jquants-mcp search <company>→ find stock codejquants-mcp price <code>→ get price historyjquants-mcp financials <code>→ get financial datajquants-mcp calendar→ check earnings dates
Setup
- Requires
JQUANTS_MAIL_ADDRESSandJQUANTS_PASSWORDenvironment variables - Free account registration: https://jpx-jquants.com/
- Python package:
pip install jquants-mcporuv tool install jquants-mcp
Terms of Service
By using this tool, you agree to the J-Quants Terms of Service. Data is for personal use only — redistribution is prohibited.
Best used for
When to use it
jquants-mcp provides command-line access to Tokyo Stock Exchange data via the official J-Quants API. It lets users search TSE-listed stocks by code or Japanese company name, retrieve daily OHLCV time series with configurable date ranges and JSON output, fetch financial summaries (revenue, profit, EP

01 · PRE-MEETING
Prepare a decision brief
Turn scattered evidence into a structured case before an investment committee meeting.

02 · TEAM WORKFLOW
Standardize handoffs
Create consistent research outputs across analysts, portfolio managers, and agents.

03 · LIVE UPDATE
Refresh the thesis
Update scenarios after a new catalyst, KPI release, or earnings result.
Community notes
Built to improve with use.
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