MCP Server¶

If your AI tool supports MCP (Model Context Protocol), you can use the official FinMind MCP server finmind-mcp instead — the tool calls it automatically and fetches real data, with no skill file to download. It is best suited to multi-turn, agentic queries and analysis.

Other connection methods

Web ChatGPT / Claude: use llms.txt — no install.
CLI tools that prefer a command file: use Agent Skill.

Installation¶

First register at FinMind to get a token, and install uv.

Claude Code (one-click): first export FINMIND_TOKEN=your_token_here, then run inside Claude Code:

/plugin marketplace add FinMind/FinMind-MCP
/plugin install finmind-mcp@finmind-official

After install, run /reload-plugins to connect and /mcp to verify. (The plugin reads ${FINMIND_TOKEN} from the environment, so export it before launching Claude Code.)

Other tools (Claude Desktop / Cursor / Windsurf / Gemini CLI): add this to the tool's MCP config file:

{
  "mcpServers": {
    "finmind": {
      "command": "uvx",
      "args": ["finmind-mcp"],
      "env": { "FINMIND_TOKEN": "your_token_here" }
    }
  }
}

Codex CLI uses a different config format ([mcp_servers] in ~/.codex/config.toml), or a one-liner: codex mcp add finmind --env FINMIND_TOKEN=... -- uvx finmind-mcp.

For per-host config file locations, the claude mcp add / gemini mcp add / codex mcp add one-liners, and verification steps, see the FinMind-MCP install guides.

Examples¶

MCP is called automatically by the tool, so just ask in natural language — no /finmind prefix needed. It is best for follow-up questions and cross-dataset agentic analysis.

Ask Directly¶

How have TSMC's stock prices trended over the past month?

Expected result: the tool automatically calls taiwan_stock_daily, returns TSMC (2330) daily prices for the past month, and summarizes the trend.

TSMC stock prices for the past month

Multi-Turn Follow-Up¶

What were 2330's institutional net buy/sell over the past week? Are foreign investors net buyers or sellers?
Then compare it with 2317 over the same period.

Expected result: it first returns TSMC institutional net buy/sell and reads the foreign-investor direction, then continues in the same conversation to query Hon Hai and compare — no need to re-enter the conditions.

Cross-Dataset Analysis¶

Analyze TSMC's stock return over the past year, compare it against monthly revenue growth over the same period, and give me a conclusion.

Expected result: the tool fetches price and monthly-revenue data separately, computes the return and YoY revenue growth, and synthesizes a written conclusion.

Conditional Screening¶

Which 5 stocks had the highest institutional net-buy value today?

Expected result: the tool queries today's institutional trading data, sorts it, and returns the top 5 stocks by net-buy value.