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funda-data

仓库创建 2026年3月14日最近提交 1 个月前SkillHot 收录 20 天前

⬈ GitHub 仓库 ⬈ SKILL.md 原文件 ⬇ Raw 原始文件

▸ 精选理由

面向分析师的综合研究面板，支持合成与纯 API 两种风格。

▸ 风险提示

需 OAuth 或 API 认证，并依赖付费/私有服务

这个 Skill 做什么

访问 Funda AI 的 MCP 与 REST 接口，提供分析合成与研究数据服务。

提供两套方式调用 Funda AI 的数据：MCP（agent_chat）用于分析合成，比如 DCF、comps、行业深度研究；REST /v1 提供实时行情、财报、期权链等原始结构化数据，需要 FUNDA_API_KEY。适合既要快速生成投研报告，又需要拿到逐条行情或财报细节时使用。特点是合成与原始数据可自由切换，覆盖从策略研究到量化数据的需求。

▸ 展开 SKILL.md 英文原文

Query Funda AI financial data via two surfaces: the MCP server at https://funda.ai/api/mcp for analyst-grade research synthesis (DCF, comps, earnings previews/recaps, sector deep-dives, SEC filings, transcripts, supply-chain mapping, ownership flow, macro framing) via the agent_chat tool — OR the REST API at https://api.funda.ai/v1 with FUNDA_API_KEY for raw data (real-time quotes, intraday candles, EOD prices, financial statements, options chains/greeks/GEX, supply-chain KG, social sentiment, news, calendars, FRED, ESG, congressional trades, AI hiring signals). Triggers: "funda", "funda.ai", real-time quote, stock price, intraday, balance sheet, income statement, options chain, DCF, comps, earnings preview/recap, analyst estimates, 10-K/10-Q/8-K, transcript, ownership flow, gamma exposure, supply chain, sector deep-dive, congressional trades, FRED. Prefer MCP for synthesis/analysis questions; use REST for raw structured data the MCP declines.

数据与抓取研究合成财务分析APIClaude Code通用

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# Funda AI Skill

Funda AI exposes two complementary surfaces backed by the same data:

| Surface | Best for | Auth | Output |
|---|---|---|---|
| **MCP** `agent_chat` at `https://funda.ai/api/mcp` | Research, analysis, synthesis | OAuth (auto via `claude mcp add`) | Synthesized text with disclaimer |
| **REST** `/v1/*` at `https://api.funda.ai` | Raw structured data | `FUNDA_API_KEY` Bearer | JSON |

Both require an active [Funda AI](https://funda.ai) subscription.

---

## Step 1: Decide Which Surface

| User wants | Surface |
|---|---|
| DCF / comps walkthrough, sector view, transcript synthesis, company primer | MCP |
| Earnings preview/recap with judgment, beat-miss decomposition, narra

via SKILL·HOT · 数据来自 GitHub 公开信息 · 原文版权归作者所有