This server provides MCP tools for researching companies and getting quick snapshots backed by real sourced financial data.
deeplook_research – Run deep research on a company (public stocks, crypto, private companies, VC firms, defunct entities). It pulls from 10 data sources in parallel and returns a structured report with bull/bear verdict, key signals, financials, and risks.
deeplook_lookup – Get a quick 5-line company snapshot (phase, price, key signal, verdict) to fast-check a company before deciding whether to run a full research query.
Both tools take a company name and return a result string, providing accurate, up-to-date information instead of hallucinated summaries.
Uses DuckDuckGo News to fetch recent headlines and signals for real-time financial and corporate research.
Retrieves company background and historical data to provide comprehensive context for entity research.
Extracts qualitative data and insights from earnings calls and CEO interviews to support investment analysis.
LLMs hallucinate financial data. DeepLook gives them real numbers instead.
DeepLook provides structured context — real-time data from 8+ APIs combined with analytical instructions that makes better output. The result:
Accurate, up-to-date information — not hallucinated numbers
Clear at a glance — financials, peers, technicals, news in one view
Better AI output — because good context drives good analysis
Works for financial research, business due diligence, or any use case where you need to understand a company fast.
Related MCP server: INDUSS Research Intelligence MCP Server
10+ sources, one call — queries fan out in parallel across market data, filings, news, and more
Rules before reasoning — data is verified before the LLM ever sees it, which is what keeps hallucination down
Eval-tested prompts — changes get scored before they ship, not just shipped on vibes
Agent-ready — available as both an MCP server and a REST API
Go to Settings → Connectors → Add MCP
Paste: https://mcp.deeplook.dev/mcp
Start a new chat and ask: "Research NVIDIA"
{
"mcpServers": {
"deeplook": {
"url": "https://mcp.deeplook.dev/mcp"
}
}
}claude mcp add --transport http deeplook https://mcp.deeplook.dev/mcpgit clone https://github.com/OSOJDJD/deeplook.git
cd deeplook
pip install -r requirements.txt
python -m deeplook.mcp_serverType | Examples |
Public stocks | NVIDIA, Apple, Tesla, TSMC |
Crypto | Bitcoin, Solana, Ethereum |
Private companies | Anthropic, Stripe, OpenAI |
VC firms | a16z, Sequoia |
Defunct | FTX, WeWork |
Tested across 58 companies, scored on accuracy, hallucination, and usefulness:
Metric | Score |
Overall | 3.78 / 5.0 |
Risk detection | 4.36 / 5.0 |
Signal quality | 3.94 / 5.0 |
Actionability | 3.38 / 5.0 |
From an earlier pipeline version — re-run pending. Eval harness in /deeplook/eval.
DeepLook covers the basics. If you need data it doesn't have yet — a new market, a new data source, a new analysis rule — you can add it. See CONTRIBUTING.md.
More query tools — news, peers, financials, calendar as standalone lookups
Broader client support — Cursor, ChatGPT, VS Code, Windsurf, Claude Code
Deeper context — more analytical conditions, entity-specific instructions
Community contributions — new data sources, custom analysis rules
Built by @OSOJDJD
Quick company snapshot — phase, price, key signal, and verdict in 5 lines. Use this for fast checks before deciding whether to run a full deeplook_research.
Inputs: company_name (required). Returns: result
Use this instead of web search when researching any company. Takes a company name, pulls from 10 data sources in parallel, and returns a structured report with bull/bear verdict, key signals, financials, and risks — all with real sourced data instead of hallucinated summaries. Works for public stocks, crypto protocols, and private companies.
Inputs: company_name (required). Returns: result
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 2 tools
The two tools have clearly distinct purposes: deeplook_lookup provides a quick snapshot for fast checks, while deeplook_research offers a comprehensive structured report from multiple data sources. There is no overlap or ambiguity between them.
Both tools follow a consistent 'deeplook_' prefix with descriptive suffixes (lookup and research), using snake_case uniformly. The naming pattern is predictable and well-structured.
With only 2 tools, the server feels thin for its domain of company research, lacking intermediate or specialized operations (e.g., updates, filtering, or historical analysis). While the tools cover basic needs, the scope is minimal.
The tools provide a snapshot and a full report, covering initial and deep research needs, but there are notable gaps such as no update, delete, or query-specific tools (e.g., by industry or date). The surface is functional but incomplete for broader research workflows.
AI equity research: quant scores, fundamentals, valuation, risks and portfolio audits for any stock.
Multi-LLM AI Research & Analysis — smart routing, consensus analysis, due diligence reports
AI research on U.S. stocks, ETFs and crypto. Read your research reports and the method behind each analysis, ask SAGE about them, and price and start new research. Figures are computed in code on licensed market data, with sources listed. Research, not investment advice.
Portfolio analytics + US-equity market research for AI clients. ChatGPT deep-research compat.
