/funda-data

name: funda-data
description: >
  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.

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, narrative framing | MCP | | Real-time or intraday quote, EOD price history | REST | | Raw options chain snapshot, greeks, GEX time series | REST | | Specific line item from a financial statement (single number, JSON) | REST | | 13F filings, insider trades, congressional trades as rows | REST | | News with structured sentiment / event timeline (JSON) | REST | | Bulk dataset downloads | REST | | AI-company hiring signals (OpenAI, Anthropic, Google, xAI) | REST |

**Default to MCP** for ambiguous research-style questions. **Use REST** when the user wants machine-readable structured data — or when the MCP refuses (real-time prices, raw quotes).

The MCP also refuses buy/sell calls, price targets, personalized portfolio advice, tax/legal advice, and trade execution. Those are out of scope for both surfaces — decline politely and don't fall through to REST hoping for a different answer.

---

Step 2: MCP Flow (Research)

2a. Verify the MCP is connected

!`claude mcp list 2>/dev/null | grep -iE "^funda:" || echo "FUNDA_MCP_NOT_CONNECTED"`

• A line starting with `funda:` → registered. The tool is callable as `mcp__funda__agent_chat`. Continue.
• `FUNDA_MCP_NOT_CONNECTED` → ask the user to install:

  claude mcp add --transport http funda https://funda.ai/api/mcp

A browser tab opens for OAuth approval (1-hour token + 30-day refresh, auto-managed). The Claude Code session may need to be restarted before the tool registers.

2b. Frame the question

`agent_chat` is a fresh research turn with **no cross-call memory** — bake the ticker, time horizon, and assumptions into the question text itself.

| User wants | Question shape | |---|---| | Earnings preview | "Preview MSFT's Q3 print Thursday — segment trends, where consensus is aggressive/conservative, beat/miss pattern." | | Earnings recap | "Walk through NVDA Q2: beat/miss by segment, guide vs consensus, transcript Q&A on data-center demand." | | Sector deep-dive | "Summarize the 2026 hyperscaler capex cycle — spending tiers by name, supplier exposure, gross-margin implications." | | Supply chain | "Map TSMC's customer concentration and N2 ramp risks — top three exposures by revenue." | | Filing summary | "Diff the new risk factors in PLTR's latest 10-K versus the prior year." | | DCF | "Walk through a DCF for NVDA assuming 25% data-center growth, 10% terminal margin, 9% WACC — surface the sensitivity table." | | Macro | "Where in the Dalio long-term debt cycle is the US, and what does that imply for duration positioning?" | | Ownership | "Has institutional ownership of CRWD shifted in the latest 13F filings — net buyers vs sellers?" |

If the user gave only a ticker, ask one clarifying question to scope the turn (preview? recap? primer? DCF?) before calling — vague questions burn a turn and return vague answers.

If the user is following up on a prior Funda response, quote the relevant paragraph back inside the new question; the agent has no memory of prior calls.

For more example questions per topic, see `references/research-topics.md`.

2c. Call the tool

mcp__funda__agent_chat(question: "<full research question>")

Typical run is 15–60 seconds; the server streams progress notifications throughout, so the client doesn't time out.

Response shape:

• `content[0].text` — answer prefixed with `[Funda research output — fundamental analysis, informational only…]`. Keep the prefix.
• `_meta["funda.io/conversation_id"]` — UUID. The in-app history page is `https://funda.ai/agent-chat?c=<id>` (the `/agent-chat` route redirects to `/agent-chat-v2?c=<id>`).
• `_meta["funda.io/timed_out"]` — `true` if the agent hit its run budget. Answer is partial; offer to retry with a tighter scope.

If the call returns 403 `subscription_required`, the MCP is registered but the account isn't subscribed — direct the user to https://funda.ai to activate.

Each call costs a research turn. Don't speculatively re-call with a rephrased question if the first answer was reasonable.

---

Step 3: REST Flow (Raw Data)

3a. Resolve FUNDA_API_KEY

The skill resolves `FUNDA_API_KEY` in this order: 1. `FUNDA_API_KEY` environment variable 2. `FUNDA_API_KEY` in `.env` in the current directory 3. `FUNDA_API_KEY` in `.env` at the git repo root