Skip to main content

DeepLook

LLMs hallucinate financial data. DeepLook gives them real numbers instead.

License: AGPL-3.0 GitHub stars

What happens when you ask "Research NVIDIA"

DeepLook Dashboard

DeepLook Analysis

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.


Get started

Claude.ai

  1. Go to Settings → Connectors → Add MCP
  2. Paste: https://mcp.deeplook.dev/mcp
  3. Start a new chat and ask: "Research NVIDIA"

Other MCP clients (Cursor, VS Code, Windsurf, Claude Desktop)

{
  "mcpServers": {
    "deeplook": {
      "url": "https://mcp.deeplook.dev/mcp"
    }
  }
}

Claude Code

claude mcp add --transport http deeplook https://mcp.deeplook.dev/mcp

Self-host

git clone https://github.com/OSOJDJD/deeplook.git
cd deeplook
pip install -r requirements.txt
python -m deeplook.mcp_server

What it covers

Type Examples
Public stocks NVIDIA, Apple, Tesla, TSMC
Crypto Bitcoin, Solana, Ethereum
Private companies Anthropic, Stripe, OpenAI
VC firms a16z, Sequoia
Defunct FTX, WeWork

Extend DeepLook

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.


Roadmap

  • 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

License

AGPL-3.0


Built by @OSOJDJD

Metadata

Release files for deeplook-research 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for deeplook-research 0.1.0
File Size Uploaded Provenance Actions
deeplook_research-0.1.0.tar.gz 113.2 kB Without provenance Details for deeplook_research-0.1.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for deeplook-research 0.1.0
File Interpreter ABI Platform Actions
deeplook_research-0.1.0-py3-none-any.whl Python 3 none any Details for deeplook_research-0.1.0-py3-none-any.whl

Total release size: 238.4 kB

Release files / deeplook_research-0.1.0.tar.gz

Download URL deeplook_research-0.1.0.tar.gz
Size 113.2 kB
Tags Source
SHA-256 checksum
How to use checksums
913e7f14fbf02369ea3bcfbfbf1e005f281e0cdf5af84e585787083d98f1c1d3
BLAKE2b-256 checksum
How to use checksums
de452147b9dfed0b611839bc1123c94eb9a5b80a818b19a6f0cd35d32f6a181a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.3

Release files / deeplook_research-0.1.0-py3-none-any.whl

Download URL deeplook_research-0.1.0-py3-none-any.whl
Size 125.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
6710d00ca1528c5f7285ddd1c5cc66d658a3dc449f2921778bcf2b62982fe956
BLAKE2b-256 checksum
How to use checksums
00584531dfaf583cf92846f0e94e04d1fb7f68ccdcd6b156fb7ccc82fd79788a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.3

Security for deeplook-research 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page