INDIVIDUAL MCP TOOL
risk_read
事件與市場結構風險:隱含波動率、注意處置、裁罰訴訟、放空限制、因子。 ★ ⚠️ **部位集中度與回撤不在這裡** —— 那是 `risk_assess` 的職責。重算一份會產生 第二個答案,而兩個都帶著我們的名字。 ★ `checked_and_clear` 是「查過而且確認沒有」(例如近一年無裁罰),和 `cannot_see` 的「不知道」是兩回事。 ★ 事實整理,不是投資建議、不是預測。輸出帶 `does_not_prove`。 ★ Args:`ticker`(例如 "2330")、`as_of`(選填)。 ★ Returns:誠實信封;事件風險 listed in `concerns`,查過確認沒有的 listed in `checked_and_clear`。 ★ PRECONDITIONS:自己取數;requires 一個已識別的 session。 ★ SIDE EFFECTS:read-only,does not 寫入。
LIVE ENDPOINT
https://mcp.twmarketdata.com/mcp
Connect to this endpoint to inspect the live schema for risk_read and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- No write-capable action terms were found; this is not proof that invocation has no side effects.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.tw-market-data]
url = "https://mcp.twmarketdata.com/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"tw-market-data": {
"type": "http",
"url": "https://mcp.twmarketdata.com/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: tw-market-data
Remote MCP URL: https://mcp.twmarketdata.com/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"tw-market-data": {
"url": "https://mcp.twmarketdata.com/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"tw-market-data": {
"type": "http",
"url": "https://mcp.twmarketdata.com/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "tw-market-data",
"transport": "streamable-http",
"url": "https://mcp.twmarketdata.com/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
list_datasets— List available Taiwan-market datasets (discovery entry point).describe_dataset— FULL semantics of one dataset: grain (what a row is), field meanings+units, ★TIME-CORRECTNESS rules (knowledge_time_field / point_in_time_safe — read before backtesting), relations for cross-table reasoning, agent_hints (when to use), quant_use (which factors).query_dataset— Query rows with built-in look-ahead protection.find_related— Traverse the knowledge graph for cross-table / supply-chain reasoning.search_filings— Semantic search over MOPS filings, financial-statement notes and company news.explain_provenance— Where did this number come from, and when could anyone have known it?get_inclusion_proof— Prove a row was in the snapshot TWMD published — and check it yourself.cite_this— Produce a bibliographic citation for TWMD data — APA, BibTeX, and a re-verifiable token.