twstock-cli 0.1.4

Agent-friendly CLI for Taiwan Stock Exchange (TWSE) and Taipei Exchange (TPEX) — stock market data, one tool

twstock-cli

Agent-friendly CLI for Taiwan Stock Exchange (TWSE) and Taipei Exchange (TPEX) — stock market data, one tool.

Install

uv (recommended)

uv tool install twstock-cli
uv tool install 'twstock-cli[mcp]'            # with MCP server support
uv tool install 'twstock-cli[mcp,analysis]'   # with everything

Homebrew

brew tap DeepWaveLab/twstock_cli https://github.com/DeepWaveLab/twstock_cli
brew install twstock-cli

pip

pip install twstock-cli
pip install 'twstock-cli[mcp]'            # MCP server support
pip install 'twstock-cli[analysis]'       # pandas, openpyxl, matplotlib, plotly
pip install 'twstock-cli[mcp,analysis]'   # everything

Update

# uv
uv tool upgrade twstock-cli

# Homebrew
brew update && brew upgrade twstock-cli

# pip
pip install --upgrade twstock-cli

From source

git clone https://github.com/DeepWaveLab/twstock_cli.git
cd twstock_cli
uv sync                                   # core only
uv sync --extra mcp --extra analysis      # with all extras

Quick Start

# Fetch daily stock data (all stocks)
twstock fetch stock.stock-day-all --json

# Filter to specific fields (saves tokens)
twstock fetch stock.stock-day-all --json --fields "Code,Name,ClosingPrice"

# Filter by stock code
twstock fetch stock.stock-day-all --json --code 2330

# Get PE ratio and dividend yield
twstock fetch stock.bwibbu-all --json --code 2330

# Discover endpoints
twstock endpoints --search "股利" --json

# Inspect endpoint schema
twstock schema stock.stock-day-all --json

Commands

twstock fetch <endpoint>

Fetch data from any TWSE/TPEX endpoint.

twstock fetch stock.stock-day-all --json              # by dotted name
twstock fetch /exchangeReport/STOCK_DAY_ALL --json     # by raw API path
twstock fetch STOCK_DAY_ALL --json                     # by API code

Flag	Description
--json	JSON envelope output (auto-detected when piped)
--fields "Code,Name"	Select specific fields
--code 2330	Filter by stock code
--limit 10	Limit records returned
--normalize	Convert strings to numbers, ROC dates to ISO 8601
--ndjson	Newline-delimited JSON (one record per line)
--raw	Bare JSON array without envelope
--dry-run	Preview request as JSON without making an HTTP call
--stdin	Read parameters from JSON on stdin
--no-cache	Bypass disk cache

twstock endpoints

Discover available endpoints.

twstock endpoints --json                           # list all 359
twstock endpoints --search "daily" --json          # search by keyword
twstock endpoints --category stock --json          # filter by category
twstock endpoints --search "bwibbu" --with-fields --json  # show fields

Sources: 143 TWSE OpenAPI + 9 TWSE Web API + 207 TPEX OpenAPI = 359 endpoints.

--category filter values: stock (45), company (86), broker (9), other (4), otc (64), otc_company (29), web (8). Use --search to find the remaining endpoints.

twstock schema <endpoint>

Inspect endpoint fields, inferred types, and example values.

twstock schema stock.stock-day-all --json

twstock serve

Start as an MCP (Model Context Protocol) server on stdio.

twstock serve

Exposes tools: twstock_fetch, twstock_endpoints, twstock_schema. Requires mcp extra.

twstock <command> --help-json

Output structured command metadata as JSON (flags, types, defaults).

twstock --help-json                  # list all commands
twstock fetch --help-json            # list fetch params with types
twstock stock --help-json            # list stock subcommands

--dry-run

Preview the planned request without making an HTTP call.

twstock fetch stock.stock-day-all --dry-run --fields "Code,Name" --code 2330

--stdin

Accept structured JSON input from stdin (CLI flags override stdin values).

echo '{"endpoint":"stock.stock-day-all","fields":["Code","Name"],"limit":5}' | twstock fetch --stdin --json

Output Formats

JSON envelope (default)

{"ok": true, "data": [{"Code": "2330", "Name": "台積電", "ClosingPrice": "595.00"}]}

NDJSON (--ndjson)

{"Code": "2330", "Name": "台積電", "ClosingPrice": "595.00"}
{"Code": "2317", "Name": "鴻海", "ClosingPrice": "100.50"}

Raw (--raw)

[{"Code": "2330", "Name": "台積電"}, {"Code": "2317", "Name": "鴻海"}]

Normalized (--normalize)

{"ok": true, "data": [{"Code": "2330", "ClosingPrice": 595.0, "TradeVolume": 36317450}]}

Environment Variables

Variable	Values	Description
TWSTOCK_OUTPUT	json, human	Override auto-detection of output format

Exit Codes

Code	Meaning
0	Success
1	API error (TWSE returned 4xx/5xx)
2	Validation error (unknown endpoint, bad args)
3	Network error (cannot reach TWSE API)

Data Analysis & Export ([analysis] extra)

Install the analysis extra to unlock data analysis, visualization, and export capabilities.

Export to XLSX

import subprocess, json, pandas as pd

result = subprocess.run(
    ["twstock", "fetch", "stock.stock-day-all", "--json", "--fields", "Code,Name,ClosingPrice,TradeVolume", "--normalize"],
    capture_output=True, text=True,
)
data = json.loads(result.stdout)["data"]
df = pd.DataFrame(data)
df.to_excel("stock_daily.xlsx", index=False)

Visualization with matplotlib

import subprocess, json, pandas as pd, matplotlib.pyplot as plt

result = subprocess.run(
    ["twstock", "fetch", "stock.stock-day-all", "--json", "--fields", "Code,Name,ClosingPrice,TradeVolume", "--normalize", "--limit", "20"],
    capture_output=True, text=True,
)
df = pd.DataFrame(json.loads(result.stdout)["data"])
df.plot.bar(x="Name", y="TradeVolume", title="Top 20 Stocks by Volume")
plt.tight_layout()
plt.savefig("volume_chart.png")

Interactive charts with plotly

import subprocess, json, pandas as pd, plotly.express as px

result = subprocess.run(
    ["twstock", "fetch", "stock.stock-day-all", "--json", "--fields", "Code,Name,ClosingPrice,TradeVolume", "--normalize", "--limit", "30"],
    capture_output=True, text=True,
)
df = pd.DataFrame(json.loads(result.stdout)["data"])
fig = px.scatter(df, x="ClosingPrice", y="TradeVolume", hover_name="Name", title="Price vs Volume")
fig.write_html("price_vs_volume.html")

Export to PPTX

from pptx import Presentation
from pptx.util import Inches
import subprocess, json

result = subprocess.run(
    ["twstock", "fetch", "stock.stock-day-all", "--json", "--fields", "Code,Name,ClosingPrice", "--limit", "10", "--normalize"],
    capture_output=True, text=True,
)
data = json.loads(result.stdout)["data"]

prs = Presentation()
slide = prs.slides.add_slide(prs.slide_layouts[5])  # blank layout
slide.shapes.title.text = "Top 10 Stocks"

rows, cols = len(data) + 1, 3
table = slide.shapes.add_table(rows, cols, Inches(0.5), Inches(1.5), Inches(9), Inches(4)).table
for i, header in enumerate(["Code", "Name", "ClosingPrice"]):
    table.cell(0, i).text = header
for r, row in enumerate(data, 1):
    for c, key in enumerate(["Code", "Name", "ClosingPrice"]):
        table.cell(r, c).text = str(row.get(key, ""))

prs.save("stocks.pptx")

Analysis extras included

Package	Purpose
pandas	DataFrames, filtering, groupby, .to_excel(), .to_csv()
openpyxl	XLSX read/write (powers pandas.to_excel())
matplotlib	Static charts and plots
plotly	Interactive HTML charts
python-pptx	PowerPoint slide generation (included in core)

For AI Agents

See AGENTS.md for agent-specific instructions, workflows, and token-saving tips.

License

MIT