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Financial Research · GitHub

FinRobot

An open-source multi-agent framework that utilizes large language models to automate complex financial analysis, including equity research and report generation.

92VF score
Maintainer
AI4Finance-Foundation
Market coverage
Global Equities, Financial Statements
GitHub stars
3,800
Updated
Verify current documentation
Best for

Automating multi-step financial research workflows and generating comprehensive institutional-grade reports.

Implementation statusGuide reviewed · Verify current documentation
Implementation status

MIT

Expected result

Multi-agent collaboration for research

Known failure mode

Requires high-tier LLM models for optimal performance

Compatibility

Global Equities, Financial Statements

Why it stands out

  • Multi-agent collaboration for research
  • Automated financial report generation
  • Market sentiment analysis
  • Technical and fundamental data integration

Risks and limitations

  • Requires high-tier LLM models for optimal performance
  • Complex initial environment setup
  • Dependent on upstream data API stability

Examples and expected outcomes

Example 1

Create a repeatable research memo

  • Sourced evidence
  • Repeatable steps
  • Explicit uncertainty
Example 2

Compare companies with one checklist

  • Sourced evidence
  • Repeatable steps
  • Explicit uncertainty
Example 3

Build a sourced bull/bear review

  • Sourced evidence
  • Repeatable steps
  • Explicit uncertainty

Access requirements

Keys and runtime

LLM API Key (OpenAI/Anthropic), Financial Data API Keys (optional)

License and data rights

MIT

Rate limits

Verify current documentation

Connect to your Agent

Claude config
pip install finrobot

# Project-scoped Agent Skill layout
.claude/skills/finrobot-review/SKILL.md
.claude/skills/finrobot-review/references/

# Restart Claude Code and confirm discovery.
Prompt example

“Use FinRobot to research AAPL. List sources and timestamps first, then separate facts, calculations, risks and missing data. Do not give personalized trading advice.”

When not to use it

  • Requires high-tier LLM models for optimal performance
  • Complex initial environment setup
  • Dependent on upstream data API stability
Installation

FinRobot

Terminal
pip install finrobot

Before you install

Review the current license and source code, pin a version, keep credentials out of prompts, and start with read-only permissions.

Project-specific questions

What can FinRobot do in a real workflow?

Multi-agent collaboration for research Automated financial report generation Market sentiment analysis Technical and fundamental data integration

What access and compatibility does FinRobot require?

MIT · Global Equities, Financial Statements

What is the main implementation risk with FinRobot?

Requires high-tier LLM models for optimal performance Complex initial environment setup Dependent on upstream data API stability

View sourceExplore agent setup templates