| 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 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"`
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:
FUNDA_API_KEY environment variableFUNDA_API_KEY in .env in the current directoryFUNDA_API_KEY in .env at the git repo root (so a worktree inherits the key from the main checkout)
!`if [ -n "$FUNDA_API_KEY" ]; then echo "KEY_FROM_ENV_VAR"; elif [ -f .env ] && grep -qE "^FUNDA_API_KEY=" .env; then echo "KEY_FROM_LOCAL_DOTENV:$(pwd)/.env"; else GIT_COMMON=$(git rev-parse --path-format=absolute --git-common-dir 2>/dev/null); if [ -n "$GIT_COMMON" ]; then ROOT=$(dirname "$GIT_COMMON"); if [ -f "$ROOT/.env" ] && grep -qE "^FUNDA_API_KEY=" "$ROOT/.env"; then echo "KEY_FROM_ROOT_DOTENV:$ROOT/.env"; else echo "KEY_NOT_SET"; fi; else echo "KEY_NOT_SET"; fi; fi`
Then act on the result:
3b. Find the right endpoint
Match the user's request to a category and read the corresponding
reference file for full parameters and response schemas.
| Category | Endpoint family | Reference |
|---|
| Real-time / batch / aftermarket quotes | /v1/quotes?type=... | references/market-data.md |
| Historical EOD, intraday candles, technical indicators | /v1/stock-price, /v1/charts | references/market-data.md |
| Commodity / forex / crypto quotes | /v1/quotes?type=commodity-quotes | references/market-data.md |
| Income / balance / cash flow / metrics / ratios | /v1/financial-statements | references/fundamentals.md |
| Company profile, peers, shares float, search, screener, list | /v1/company-profile, /v1/company-details, /v1/search, /v1/companies | references/fundamentals.md |
| Analyst estimates, price targets, grades, DCF, ratings | /v1/analyst?type=... | references/fundamentals.md |
| Options chain, greeks, GEX, IV, max pain, flow, screener | /v1/options/... | references/options.md |
| Supply-chain KG: suppliers, customers, competitors, partners | /v1/supply-chain/... | references/supply-chain.md |
| Twitter, Reddit, Polymarket, government trading, ownership | /v1/twitter-posts, /v1/reddit-posts, /v1/polymarket/..., /v1/government-trading, /v1/ownership | references/alternative-data.md |
| AI-enriched news + aggregated sentiment + event timeline | /v1/news/ticker, /v1/news/timeline, /v1/news/sentiment | references/news-enriched.md |
| SEC filings, earnings/podcast transcripts, research reports | /v1/sec-filings, /v1/transcripts, /v1/investment-research-reports | references/filings-transcripts.md |
| Earnings / dividend / IPO / splits / economic calendar | /v1/calendar?type=... | references/calendar-economics.md |
| Treasury rates, GDP/CPI indicators, FRED, risk premium | /v1/economics, /v1/fred | references/calendar-economics.md |
| Stock news, gainers/losers, ETF holdings, ESG, COT, bulk, market hours | /v1/news, /v1/market-performance, /v1/funds, /v1/esg, /v1/cot-report, /v1/bulk, /v1/market-hours | references/other-data.md |
| AI-company hiring signals (OpenAI, Anthropic, Google, xAI, Mercor, SurgeAI) | /v1/recruit-... | references/recruit.md |
| Claude API proxy via Bedrock | /v1/claude/v1/messages | references/claude-proxy.md |
3c. Call the endpoint
curl -s -H "Authorization: Bearer $FUNDA_API_KEY" \
"https://api.funda.ai/v1/<endpoint>?<params>" | python3 -m json.tool
All responses are {"code": "0", "message": "", "data": ...}. A non-zero
code is an error — read message.
List endpoints paginate: {"items": [...], "page": 0, "page_size": 20, "next_page": 1, "total_count": N}. Pages are 0-based; next_page is -1 when exhausted.
For broad ticker overviews ("tell me about AAPL"), combine a few REST
calls: /v1/company-profile for sector/CEO/mcap/price + /v1/financial-statements?type=key-metrics-ttm + /v1/analyst?type=price-target-summary.
Step 4: Respond to the User
- For MCP synthesis: surface with structure (tables, bullets, headings) — don't dump the raw blob. Preserve the Funda disclaimer; never repackage analysis as a recommendation, price target, or trade signal.
- For MCP responses, cite
https://funda.ai/agent-chat?c={conversation_id} so the user can inspect the agent's full timeline.
- For REST responses, format numbers cleanly (prices to 2 decimals, ratios to 2-4, large numbers with commas or abbreviations like
$2.8T). Use tables for comparative data; summarize trends rather than dumping time series.
- For DCF / valuation work, surface the assumptions Funda used so the user can adjust them.
- Note the source: "Funda AI" (whether MCP or REST).
- Never provide trading recommendations — present the data and let the user draw conclusions.
Reference Files
MCP path:
references/research-topics.md — categorized example questions and tips for framing agent_chat queries.
REST path:
references/market-data.md — quotes, historical prices, charts, technical indicatorsreferences/fundamentals.md — financial statements, company profile/details, search/screener, analyst, companies listreferences/options.md — chains, greeks, GEX, flow, IV, screener, contract-level datareferences/supply-chain.md — supply-chain KG, relationships, graph traversalreferences/alternative-data.md — Twitter, Reddit, Polymarket, government trading, ownershipreferences/news-enriched.md — AI-enriched news, event timeline, aggregated sentimentreferences/filings-transcripts.md — SEC filings, earnings/podcast transcripts, research reportsreferences/calendar-economics.md — calendars, economics, treasury, FREDreferences/other-data.md — news, market performance, funds, ESG, COT, bulk, market hoursreferences/recruit.md — AI-company hiring signals, JD classifications, product clusters, launch probabilitiesreferences/claude-proxy.md — Claude API proxy via Bedrock
