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virattt

virattt/dexter

An autonomous AI agent for deep financial research that plans tasks, self-checks its work, and pulls live market data.

Open-source alternative to:Bloomberg Terminal

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What is it?

Dexter is a terminal-based financial research agent written in TypeScript and run with Bun. Given a financial question, it breaks the request into structured research steps, selects tools to gather data, checks its own intermediate results, and iterates until it produces a data-backed answer. It is positioned as a Claude Code-style agent specialized for finance.

The agent has access to financial data such as income statements, balance sheets, and cash flow statements through the Financial Datasets API, and can run web search through Exa or Tavily. It supports several LLM providers, including OpenAI, Anthropic, Google, xAI, OpenRouter, and local Ollama models. Safety limits such as loop detection and step caps guard against runaway execution.

The project also includes an evaluation suite that scores the agent against a dataset of financial questions using LangSmith tracing and an LLM-as-judge approach, plus a scratchpad that logs every tool call to JSONL files for debugging. An optional WhatsApp gateway lets you send questions to the agent from your own chat. The project is explicitly for educational and informational use and is not intended for real investment decisions.

Key features

  • 01Breaks complex financial questions into step-by-step research plans
  • 02Pulls income statements, balance sheets, and cash flow statements
  • 03Checks its own results and iterates until the answer is complete
  • 04Supports multiple LLM providers, including local Ollama models
  • 05Logs every tool call to scratchpad files for debugging
  • 06Includes an evaluation suite with LangSmith tracing

Use cases

  • Researching a public company's historical financial statements from a terminal
  • Studying how an AI agent plans and uses tools for data-heavy analysis
  • Benchmarking LLM agents on financial question datasets
  • Chatting with a financial research agent through WhatsApp

Quick start

  1. 1

    Install the Bun runtime (v1.0 or higher) from bun.com

  2. 2

    Clone the repository

    git clone https://github.com/virattt/dexter.git
  3. 3

    Install dependencies with Bun

    bun install
  4. 4

    Run Dexter in interactive mode

    bun start

Things to know

  • Requires an OpenAI API key and a Financial Datasets API key, which may carry costs.
  • The README says it is for educational and informational use only and is not meant for real trading or investment.
  • Outputs may be incorrect or out of date, so verify results before relying on them.

Topics

FAQ

What is dexter?
An autonomous AI agent for deep financial research that plans tasks, self-checks its work, and pulls live market data. Dexter is a terminal-based financial research agent written in TypeScript and run with Bun. Given a financial question, it breaks the request into structured research steps, selects tools to gather data, checks its own intermediate results, and iterates until it produces a data-backed answer. It is positioned as a Claude Code-style agent specialized for finance.
Is dexter free to use? What license does it have?
dexter has no declared license. Its code is public, but without a license you have no explicit permission to reuse it; ask the author before relying on it.
Is dexter still maintained?
Updated within 6 months. The last commit to dexter was on Sep 23, 2026.
What can I use dexter for?
Researching a public company's historical financial statements from a terminal Studying how an AI agent plans and uses tools for data-heavy analysis Benchmarking LLM agents on financial question datasets Chatting with a financial research agent through WhatsApp
How do I install dexter?
Install the Bun runtime (v1.0 or higher) from bun.com Clone the repository: git clone https://github.com/virattt/dexter.git Install dependencies with Bun: bun install Run Dexter in interactive mode: bun start
Where can I get dexter?
The source code and installation instructions are on GitHub: https://github.com/virattt/dexter

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