# ai-berkshire MCP Client: Value Investing with Claude Code & Codex

> ai-berkshire is an MCP Client that provides a value investing research framework, integrating methodologies from four masters via AI agents. It's designed for Claude Code and Codex users seeking to automate and deepen their investment analysis.

**Published:** 2026-08-07T12:00:24.934+00:00

**Keywords:** ai-berkshire,mcp-client,value-investing,claude-code,codex

# ai-berkshire: Value Investing Research with Claude Code and Codex

The `ai-berkshire` MCP Client brings a structured, multi-agent approach to value investing research directly into Claude Code and Codex environments. This Python-based client systematizes the methodologies of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu, enabling AI agents to conduct professional-grade investment analysis. It transforms a single user with an LLM client into a full investment research team, with reported real-world returns.

## Integrating Investment Skills with Claude Code

`ai-berkshire` is designed to extend Claude Code's capabilities by injecting a suite of investment research skills directly into its global command directory. This integration allows users to invoke specialized research functions as native commands within Claude Code.

To install these skills for Claude Code on macOS or Linux, navigate to the `ai-berkshire` directory after cloning the repository and execute:

```bash
./scripts/install-claude-commands.sh
```

Windows users leveraging PowerShell or Command Prompt can achieve the same by running:

```bat
git clone https://github.com/xbtlin/ai-berkshire.git
cd ai-berkshire
.\scripts\install-claude-commands.bat
```

Once installed, these skills are available for direct invocation within Claude Code, providing an `/investment-research` experience.

## Connecting to Codex with Prompts and Skills

For Codex users, `ai-berkshire` offers two distinct integration paths: a set of "skills" and an optional layer of "slash prompts." The skills are designed to provide a similar `/investment-research` experience to Claude Code.

Codex users on macOS or Linux can install the core skills by running:

```bash
./scripts/install-codex-prompts.sh
```

Windows users can install the Codex skills via PowerShell or Command Prompt:

```bat
git clone https://github.com/xbtlin/ai-berkshire.git
cd ai-berkshire
.\scripts\install-codex-skills.bat
```

Additionally, an optional set of Codex slash prompts can be installed on Windows for further compatibility:

```bat
REM Optional: Install Codex slash prompts
.\scripts\install-codex-prompts.bat
```

The repository maintains three distinct entry points for these integrations: `skills/*.md` are the source files for Claude Code commands, `codex-skills/*/SKILL.md` are generated from `skills/*.md` by `scripts/sync-codex-skills.py` for Codex skill packages, and `codex-prompts/*.md` provide the optional Codex slash prompt compatibility layer.

## Core Capabilities and Framework Design

`ai-berkshire` provides a collection of investment research skills that operationalize the methodologies of four renowned value investors. The client leverages multi-agent adversarial analysis to conduct professional-grade research, aiming to redefine the depth and efficiency of investment analysis through AI.

The framework's design is not merely theoretical; it is backed by a real track record. The project reports a +69.29% return for 2024 and +66.38% for 2025, significantly outperforming major indices like the S&P 500, Hang Seng Index, CSI 300, and Nasdaq over the same periods. These figures, derived from a real Futu Securities account, demonstrate the practical application and effectiveness of the AI-driven research framework.

The full framework and comprehensive reports are maintained within the `ai-berkshire` repository.

## References

- [ai-berkshire on GitHub](https://github.com/xbtlin/ai-berkshire)
- [Model Context Protocol Documentation](https://modelcontextprotocol.io/introduction)
- [ai-berkshire on model-context-protocol.com](https://model-context-protocol.com/clients/)
```

## Related Repository

- [ai-berkshire](https://model-context-protocol.com/clients/ai-berkshire)

**Source:** https://model-context-protocol.com/blog/ai-berkshire-mcp-client-value-investing-with-claude-code-codex-mcp-client-guide