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Core data

Market & prices

TWSE / TPEx daily bars, adjusted prices, indices, and market breadth

Financials & growth

Monthly revenue, the three financial statements, financial metrics, and valuation data

Flows & positioning

Institutional investors and margin & short-selling data

Company & structure

Company & events

Company profiles, disclosures, events, corporate actions, and dividends

Taxonomy & structure

Theme taxonomy, index classification, and cross-dataset mapping

Strategy & quant

Features, factor data, time alignment, and screener

Platform capabilities

API access

REST API, authentication, and your first request

Query & tools

Search API, Query API, field lists, and query examples

Tools / MCP

Agent workflows, MCP tools, and the OpenAPI entry point

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Documentation

DASHBOARD

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FOR AI AGENTS

MCP Serverllms.txtTool manifestOpenAPI SpecAgent workflow examples
WebhooksBuilding

OVERVIEW

OverviewQuick startAuthenticationSource policyData gradesData lineageMarket coverage

DATA APIS

GUIDES

How to get the 3 financial statementsHow to read institutional flowsHow to check market statusHow to wire a strategy / AI agent

SDKS

Release statusPython SDKJavaScript / TypeScript SDK

Building an AI agent? Start with /llms.txt for the full site index.

For AI agents

MCP Server

Beta — the hosted MCP server is live and connectable, but not yet GA.

Status — Beta

The hosted MCP server is live at mcp.twmarketdata.com/mcp and connectable today. It is beta, not GA — the surface may change before general availability, and the REST API remains the stable path.

Connect

It speaks streamable-HTTP MCP and authenticates with your X-API-Key. With Claude Code:

claude mcp add --transport http tw-market-data \  https://mcp.twmarketdata.com/mcp \  --header "X-API-Key: sk_live_..."

The tools it exposes

Server tw-market-data (v1.28.1) exposes four tools; an agent discovers them automatically after connecting:

  • list_datasets — discovery entry point. Lists the available datasets (id / name / category / tier / one-line description). Use this first to find the right data.
  • describe_dataset — full semantics of one dataset: grain (what a row is), field meanings + units, time-correctness rules (point-in-time safety — read before backtesting), relations and agent hints.
  • query_dataset — query rows with built-in look-ahead protection. Pass as_of (YYYY-MM-DD) for backtesting: rows are filtered by disclosure date ≤ as_of, so the agent only sees what was public then.
  • find_related — traverse the knowledge graph for cross-table / supply-chain reasoning: dataset_id returns join-able datasets; ticker returns its industry value-chain node + peers.
  • Same official data and same credits as REST — the MCP tools are a protocol wrapper, not a separate dataset. (Descriptions above are pulled from the live server, not paraphrased.)

English is a semantic rewrite, not a machine translation.

On this page

  • Status — Beta
  • Connect
  • The tools it exposes