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Get Started Free →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, n
.claude/skills/himself65-funda-data/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-06 | ✗→✓ | ▲ Improved | 74% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 33% | 0% |
| case-05 | ✓→✗ | ▼ Worse | 70% | 0% |
| case-16 | ✓→✗ | ▼ Worse | 45% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 810% | 0% |
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.
| 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.
!`claude mcp list 2>/dev/null | grep -iE "^funda:" || echo "FUNDA_MCP_NOT_CONNECTED"`funda: → registered. The tool is callable as mcp__funda__agent_chat. Continue.FUNDA_MCP_NOT_CONNECTED → ask the user to install:bash 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.
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.
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.
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:
KEY_FROM_ENV_VAR — use $FUNDA_API_KEY directly in curl calls.KEY_FROM_LOCAL_DOTENV:<path> / KEY_FROM_ROOT_DOTENV:<path> — load once before calling:bash export FUNDA_API_KEY=$(grep -E "^FUNDA_API_KEY=" <path> | head -1 | cut -d= -f2- | sed 's/^["'\'']//;s/["'\'']$//')
KEY_NOT_SET — ask the user for their key. They can either export FUNDA_API_KEY="..." or add FUNDA_API_KEY=... to .env at the repo root (preferred for worktrees).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 |
bashcurl -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.
https://funda.ai/agent-chat?c={conversation_id} so the user can inspect the agent's full timeline.$2.8T). Use tables for comparative data; summarize trends rather than dumping time series.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| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 26,414 | 6,358 | -76% | 1 | 1 | 0% | 4,477 | 3,602 | -20% | 0 | 0 | — |
case-02 | fail→fail | 12,125 | 7,629 | -37% | 1 | 1 | 0% | 2,702 | 3,647 | +35% | 0 | 0 | — |
case-03 | fail→fail | 14,610 | 6,769 | -54% | 1 | 1 | 0% | 2,709 | 3,700 | +37% | 0 | 0 | — |
case-04 | pass→pass | 5,900 | 2,160 | -63% | 1 | 1 | 0% | 393 | 3,576 | +810% | 0 | 0 | — |
case-05 | pass→fail | 13,916 | 11,447 | -18% | 1 | 1 | 0% | 2,295 | 3,903 | +70% | 0 | 0 | — |
case-06 | fail→pass | 13,061 | 6,180 | -53% | 1 | 1 | 0% | 2,422 | 4,226 | +74% | 0 | 0 | — |
case-07 | fail→fail | 21,335 | 4,421 | -79% | 1 | 1 | 0% | 4,068 | 3,455 | -15% | 0 | 0 | — |
case-08 | fail→fail | 16,103 | 4,768 | -70% | 1 | 1 | 0% | 2,938 | 3,542 | +21% | 0 | 0 | — |
case-09 | fail→fail | 16,925 | 35,865 | +112% | 1 | 1 | 0% | 3,055 | 4,194 | +37% | 0 | 0 | — |
case-10 | fail→fail | 20,402 | 6,373 | -69% | 1 | 1 | 0% | 3,545 | 3,674 | +4% | 0 | 0 | — |
case-11 | fail→fail | 13,072 | 4,668 | -64% | 1 | 1 | 0% | 2,297 | 3,487 | +52% | 0 | 0 | — |
case-12 | fail→fail | 7,857 | 4,599 | -41% | 1 | 1 | 0% | 1,773 | 3,522 | +99% | 0 | 0 | — |
case-13 | fail→pass | 13,180 | 4,923 | -63% | 1 | 1 | 0% | 3,239 | 4,301 | +33% | 0 | 0 | — |
case-14 | fail→fail | 12,484 | 7,054 | -43% | 1 | 1 | 0% | 2,772 | 3,670 | +32% | 0 | 0 | — |
case-15 | fail→fail | 10,903 | 6,169 | -43% | 1 | 1 | 0% | 2,449 | 3,568 | +46% | 0 | 0 | — |
case-16 | pass→fail | 11,159 | 7,221 | -35% | 1 | 1 | 0% | 2,585 | 3,740 | +45% | 0 | 0 | — |
case-17 | fail→fail | 8,974 | 5,954 | -34% | 1 | 1 | 0% | 2,156 | 3,604 | +67% | 0 | 0 | — |
case-18 | fail→fail | 21,433 | 5,099 | -76% | 1 | 1 | 0% | 5,418 | 3,614 | -33% | 0 | 0 | — |
case-19 | fail→fail | 7,124 | 6,073 | -15% | 1 | 1 | 0% | 375 | 3,600 | +860% | 0 | 0 | — |
case-20 | fail→fail | 28,359 | 4,289 | -85% | 1 | 1 | 0% | 4,694 | 3,457 | -26% | 0 | 0 | — |
case-21 | fail→fail | 13,024 | 5,665 | -57% | 1 | 1 | 0% | 2,676 | 3,545 | +32% | 0 | 0 | — |
case-22 | fail→fail | 11,992 | 6,149 | -49% | 1 | 1 | 0% | 2,465 | 3,767 | +53% | 0 | 0 | — |
case-23 | fail→fail | 14,589 | 6,709 | -54% | 1 | 1 | 0% | 2,604 | 3,539 | +36% | 0 | 0 | — |
case-24 | fail→fail | 4,898 | 6,710 | +37% | 1 | 1 | 0% | 1,138 | 3,610 | +217% | 0 | 0 | — |
case-25 | fail→fail | 15,228 | 4,120 | -73% | 1 | 1 | 0% | 2,833 | 3,441 | +21% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted, and 3 counted toward the lift figure. The other 22 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of 0 percentage points is the difference between those two pass rates over the 3 comparable cases. 6 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.