Defeatbeta API MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
pip install defeatbeta-api
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add defeatbeta-api -- node "<FULL_PATH_TO_DEFEATBETA_API>/dist/index.js"

Replace <FULL_PATH_TO_DEFEATBETA_API>/dist/index.js with the actual folder you prepared in step 1.

README.md

An open-source alternative to Yahoo Finance's market data APIs

Defeat Beta API

An open-source alternative to Yahoo Finance's market data APIs with higher reliability.

See the example guide for detailed usage instructions, and try it out directly in an interactive environment using .

The list of changes can be found in the Changelog

Introduction

High-Performance & Reliable Data Engine: Provides a stable, reproducible market data source fully hosted on Hugging Face’s yahoo-finance-data dataset—eliminating scraping issues and rate limits. Powered by DuckDB’s OLAP engine and the `cache_httpfs` extension, the system delivers sub-second analytical queries with full SQL compatibility, giving you a unified, high-performance workflow for large-scale financial data.

Extended Financial Data: Includes TTM EPS, TTM PE, Market Cap, PS Ratio, PB Ratio, PEG Ratio, ROE, ROIC, WACC, ROA, Equity Multiplier, Assert Turnover, SEC Filings, Earnings call transcripts, Stock News, Revenue by segment and Revenue by geography etc. (continuously expanding).

Automated DCF Valuation: Generate comprehensive Discounted Cash Flow (DCF) analysis with professional Excel output. Automatically calculates WACC, projects 10-year cash flows, estimates enterprise value and fair price, and provides buy/sell recommendations—all in a ready-to-use, fully editable spreadsheet.

LLM-Powered Analysis: Use Large Language Models (LLMs) to analyze earnings call transcripts, quarterly financial changes, and quarterly forecasts to extract key data, understand metric changes, and interpret forecast drivers.

MCP Server implementation: A MCP server implementation for defeatbeta-api, provides AI access analysis through MCP. Click here to discover more ways to use MCP.

Skills implementation: A Skills implementation for defeatbeta-api, enhances AI financial analysis capabilities with professional workflows. Compatible with Claude.ai, Manus, and other AI platforms that support skills.

Quickstart

Installation

Install defeatbeta-api from PYPI using pip:

MacOS / Linux

$ pip install defeatbeta-api

Windows

⚠️ Requires WSL/Docker Due to dependencies on cache_httpfs (unsupported on Windows):

Option 1: WSL (Recommended)

  1. Install WSL
  2. In WSL terminal:
$ pip install defeatbeta-api

Option 2: Docker

  1. Install Docker Desktop
  2. Run in Linux container:
docker run -it python:latest pip install defeatbeta-api

Usage

Insta

Tools (3)

get_financial_dataRetrieve historical and current financial metrics including EPS, PE, Market Cap, and more.
run_dcf_analysisPerform a Discounted Cash Flow analysis for a given stock ticker.
get_earnings_transcriptAccess earnings call transcripts for a specific company.

Configuration

claude_desktop_config.json
{"mcpServers": {"defeatbeta-api": {"command": "python", "args": ["-m", "defeatbeta_api.mcp"]}}}

Try it

Perform a DCF analysis for AAPL and summarize the fair price estimate.
What is the current TTM PE ratio for NVDA compared to its historical average?
Analyze the latest earnings call transcript for MSFT to identify key growth drivers.
Retrieve the revenue by geography for TSLA for the last fiscal year.

Frequently Asked Questions

What are the key features of Defeatbeta API?

High-performance data engine powered by DuckDB. Automated Discounted Cash Flow (DCF) valuation with Excel output. Access to extended financial data like TTM EPS, ROE, and WACC. LLM-powered analysis of earnings transcripts and quarterly forecasts.

What can I use Defeatbeta API for?

Automating financial research and stock valuation workflows. Generating professional-grade DCF models for investment analysis. Extracting insights from complex earnings call transcripts using LLMs. Performing large-scale historical financial data analysis without rate limits.

How do I install Defeatbeta API?

Install Defeatbeta API by running: pip install defeatbeta-api

What MCP clients work with Defeatbeta API?

Defeatbeta API works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep Defeatbeta API docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare