🔍 DeepLook

Free Bloomberg Terminal for AI Agents — open-source MCP server that researches any company in under a minute.

LLMs hallucinate financial data. Other finance MCP servers return raw data from a single source — you still do the research yourself. DeepLook runs the full workflow: 10 sources in parallel, cross-referenced, with a structured bull/bear verdict. One call, in under a minute, no API keys needed.

<p align="center">

<br>
<em>Ask "research NVIDIA" → get this in under a minute</em>
</p>

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⚡ Getting Started

Hosted (30 seconds)

1. Claude.ai → Settings → Connectors → Add MCP Server
2. Paste: https://mcp.deeplook.dev/mcp
3. Try: "Use DeepLook to research NVIDIA"

Works with Claude Desktop, Cursor, Windsurf, or any MCP-compatible client.

Self-Host

1. Clone and install:

git clone https://github.com/OSOJDJD/deeplook.git
cd deeplook
python3 -m venv venv && source venv/bin/activate
pip install -e .
cp .env.example .env   # add at least one LLM key

2. Run as HTTP MCP server:

python -m deeplook.mcp_server --http --port 8819

3. Or add to Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "deeplook": {
      "command": "/full/path/to/deeplook/venv/bin/python",
      "args": ["-m", "deeplook.mcp_server"],
      "cwd": "/full/path/to/deeplook",
      "env": { "ANTHROPIC_API_KEY": "sk-ant-..." }
    }
  }
}

CLI (no MCP):

python -m deeplook "NVIDIA"
python -m deeplook "Aave"
python -m deeplook "Anthropic"

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What You Get

NVIDIA Corporation — $181.93 | EXPANDING / ACCELERATING
Key Signals:
🟢 Jensen Huang projects $1T AI chip revenue by 2027

🟢 Vera Rubin platform with 7 new chips in production

🔴 Earnings surprise: -55.03%
Verdict: Mega-cap AI leader with 73% revenue growth, $1T opportunity
🟢 Revenue +73.2% YoY, earnings +95.6%, $58.1B FCF

🔴 RSI 37.2 oversold, $4.42T valuation limits upside

⏳ Wait for: Q1 FY2027 earnings on 2026-05-20

Embedded structured JSON with precise metrics, peer comparison, technicals
→ AI clients auto-render as interactive dashboards

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Features

- 10+ data sources in parallel (yfinance, news, CoinGecko, DeFiLlama, SEC EDGAR, Wikipedia, YouTube, etc.)
- Works for public stocks, crypto, and private companies
- Dual output: human-readable summary + structured JSON for AI agents
- Bull/bear verdict with catalyst timeline
- Peer comparison with financial metrics
- Lookup in seconds · full research in under a minute
- Two tools: deeplook_research (full report) and deeplook_lookup (quick snapshot)

Supported Entity Types

Public Equity · Crypto/DeFi · Private Companies · Exchanges · VCs · Foundations

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API Keys

Pick at least one LLM provider:

| Variable | Provider |
|----------|----------|
| ANTHROPIC_API_KEY | Claude — Haiku + Sonnet (recommended) |
| OPENAI_API_KEY | GPT-4o-mini |
| GEMINI_API_KEY | Gemini 2.0 Flash Lite |
| DEEPSEEK_API_KEY | DeepSeek Chat |

Optional (for deeper research):

| Variable | Description |
|----------|-------------|
| TAVILY_API_KEY | Search fallback when DDG is rate-limited |
| COINGECKO_API_KEY | CoinGecko Pro for crypto data |
| ROOTDATA_SKILL_KEY | RootData for crypto project data |

Cost per report: ~$0.02–0.05 (Anthropic) · ~$0.01–0.03 (OpenAI) · ~$0.01–0.02 (Gemini) · ~$0.005–0.01 (DeepSeek)

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Data Sources

| Source | Used For |
|--------|----------|
| yFinance | Price, financials, analyst targets, technicals |
| DuckDuckGo News | Recent signals, headlines |
| Wikipedia | Company background |
| YouTube | Earnings calls, CEO interviews |
| CoinGecko | Token price, market cap, volume |
| RootData | Crypto funding, team data |
| DefiLlama | TVL, chain metrics |
| SEC EDGAR | 10-K, 10-Q, 8-K filings |
| Finnhub | Earnings, news, sentiment |
| Website | Investor relations, product pages |

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How It Works

Company Name
    ↓
Entity Type Router  (public equity / crypto / private / exchange / VC / foundation)
    ↓
10 Parallel Fetchers  (DDG News, yFinance, CoinGecko, SEC EDGAR, ...)
    ↓
3-Call LLM Pipeline:  Extract (Haiku)  →  Judge (Sonnet)  →  Act (Sonnet)
    ↓
Structured Report + Embedded JSON

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Eval

Tested across 58 companies (US mega-cap, growth stocks, crypto, pre-IPO, international, edge cases):

| Metric | Score |
|--------|-------|
| Overall | 3.78 / 5.0 |
| Risk detection | 4.36 / 5.0 |
| Signal quality | 3.94 / 5.0 |
| Actionability | 3.38 / 5.0 |

Eval framework ships in /eval — run it yourself, contribute ground truth data.

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License

MIT — use it however you want.

Built by @tysenpa1 · Open an issue if something breaks or a report looks wrong.