Funda Data
Query Funda AI for analyst-style earnings research, SEC summaries, and structured market data when building or validating finance-heavy products.
Overview
Funda Data is an agent skill most often used in Idea (also Validate, Grow) that queries Funda AI via MCP synthesis or 60+ REST endpoints for market and company data.
Install
npx skills add https://github.com/himself65/finance-skills --skill funda-dataWhat is this skill?
- Dual surface: Funda MCP agent_chat for research synthesis plus REST API with 60+ endpoints for raw JSON
- MCP path covers earnings, SEC filings, transcripts, comps/DCF framing, and macro sector narratives
- REST fallback for real-time quotes, statements, options chains, supply-chain graph edges, and alt-data feeds
- Triggers on funda, funda.ai, or specific financial data topics in conversation
- OAuth for MCP via claude mcp add; Bearer FUNDA_API_KEY for REST
- 60+ REST API endpoints at api.funda.ai/v1
- MCP server at funda.ai/api/mcp with agent_chat tool
Adoption & trust: 738 installs on skills.sh; 2.7k GitHub stars; 0/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need earnings context, filings, or live market JSON but do not want to stitch dozens of finance APIs and prompts by hand.
Who is it for?
Solo builders prototyping fintech agents, investment memos, or validation models that cite real market and filing data.
Skip if: Teams without Funda access who only need generic web search or one-off stock tickers with no structured API requirement.
When should I use this skill?
User mentions funda, funda.ai, or asks for earnings, SEC, sector, macro, or raw market/options data Funda exposes.
What do I get? / Deliverables
Your agent returns Funda-backed research synthesis or structured datasets ready for dashboards, memos, or downstream validation steps.
- Funda MCP research synthesis or REST JSON payloads
- Ticker- or sector-scoped financial datasets for downstream tools
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Financial and competitive research is where solo builders first need institutional-grade data before they commit to a niche or pricing model. The skill’s MCP path is built for synthesis questions—earnings previews, sector deep-dives, and company primers—that match early opportunity research.
Where it fits
Draft a semiconductor sector deep-dive and supply-chain map before choosing a B2B data product angle.
Compare comps and estimate-revision trends to sanity-check a fintech SaaS price point.
Refresh earnings recap copy in a user-facing dashboard using MCP synthesis.
How it compares
Use instead of generic LLM financial guessing when you want a dedicated Funda MCP plus REST fallback contract.
Common Questions / FAQ
Who is funda-data for?
Indie developers and small teams building research agents, trading tools, or validation workflows that need Funda AI as a structured data backbone.
When should I use funda-data?
During idea research for sector and company primers, at validate for pricing and competitive signals, and in grow when you refresh earnings or macro framing for content or analytics features.
Is funda-data safe to install?
Review the Security Audits panel on this Prism page and treat API keys and OAuth tokens as secrets with least-privilege Funda accounts.
SKILL.md
READMESKILL.md - Funda Data
# Funda Data Query [Funda AI](https://funda.ai) financial data via two complementary surfaces: - **MCP server** at `https://funda.ai/api/mcp` — single `agent_chat` tool for analyst-grade research synthesis. OAuth (auto via `claude mcp add`). - **REST API** at `https://api.funda.ai/v1` — 60+ endpoints for raw structured data. `FUNDA_API_KEY` Bearer auth. The skill prefers the MCP for research/analysis questions and falls back to REST for raw data the MCP declines (real-time quotes, intraday candles, raw options chains, single line items, bulk downloads). ## Triggers **MCP path** (synthesis): - Earnings previews/recaps, beat-miss decomposition - Analyst estimate-revision trends - SEC filing summaries (10-K, 10-Q, 8-K, S-1) - Earnings call transcript digestion - Company primers, competitive positioning, supply-chain mapping - Sector deep-dives (semis, pharma, banks, retail, energy, mining, housing) - DCF and comps modelling against caller-supplied assumptions - Macro framing (Fed stance, Dalio quadrant, sector rotation) **REST path** (raw data): - Real-time / intraday / EOD prices and quotes - Financial statements (income, balance sheet, cash flow) as structured JSON - Options chains, greeks, GEX, IV, max pain, flow alerts - Supply-chain knowledge graph (raw edges) - Twitter, Reddit, Polymarket, congressional trades, ownership (13F) - News, calendars, FRED, ESG, COT, AI-company hiring signals Triggers on any mention of "funda", "funda.ai", or specific endpoints/topics above. ## Out of Scope (Both Surfaces) The Funda agent (and this skill) will not: - Issue buy / sell / hold recommendations or price targets - Provide personalized investment advice or portfolio allocation - Give tax, legal, or regulatory advice - Execute trades ## Platform **CLI only** — requires Claude Code (or another MCP-aware client with shell access) so `claude mcp add` and the curl-based REST flow both work. ## Setup > **Paid service** — A [Funda AI](https://funda.ai) subscription is required. The MCP returns 403 `subscription_required` and the REST API rejects unsubscribed keys. ### MCP ```bash claude mcp add --transport http funda https://funda.ai/api/mcp ``` A browser tab opens for OAuth. The access token lasts 1 hour and auto-refreshes via a 30-day refresh token. Restart your Claude Code session after approval so the tool registers. To remove later: `claude mcp remove funda`. ### REST Get an API key from Funda AI, then either: ```bash export FUNDA_API_KEY="your-api-key-here" ``` …or add `FUNDA_API_KEY=...` to `.env` at the repo root (preferred when working across worktrees — the skill resolves the key from env, local `.env`, then the repo-root `.env`). ## Reference Files | File | Path | Description | |---|---|---| | `references/research-topics.md` | MCP | Example research questions per topic and framing tips for `agent_chat` | | `references/market-data.md` | REST | Quotes, historical prices, charts, technical indicators | | `references/fundamentals.md` | REST | Financial statements, company details, search/screener, analyst data | | `references/options.md` | REST | Chains, greeks, GEX, flow, IV, screener, contracts | | `references/supply-chain.md` | REST | Supply-chain KG, relationships, graph traversal | | `references/alternative-data.md` | REST | Twitter, Reddit, Polymarket, government trading, ownership | | `references/news-enriched.md` | REST | AI-enriched news, event timeline, aggregated sentiment | | `references/filings-transcripts.md` | REST | SEC filings, earnings/podcast transcripts, research reports | | `references/calendar-economics.md` | REST | Calendars, economics, treasury, FRED | | `references/other-data.md` | REST | News, market performance, funds, ESG, COT, bulk | | `references/recruit.md` | REST | AI-company hiring signals | | `references/claude-proxy.md` | REST | Claude API proxy via Bedrock | # Alternative Data Reference Social sentiment (Twitter, Reddit), prediction markets (Polymarket), government trading,