What is Peer Review Mcp

peer-review-mcp is an MCP server that allows AI agents to seek assistance or feedback from more capable models when evaluating their plans or solving problems.

Use cases

Use cases include AI agents requesting feedback on project plans, seeking expert guidance on complex issues, and enhancing collaborative efforts among different AI models.

How to use

To use peer-review-mcp, install the necessary packages using ‘npm ci’ and ‘npm run build’. Then, configure the MCP server by adding the required settings in the configuration file, including the path to the repository and the helper model API key.

Key features

Key features include the ability to ask for peer reviews on plans and seek expert help for challenging problems, enabling collaboration between AI agents and advanced models.

Where to use

peer-review-mcp can be used in various fields such as AI development, research, and any domain where AI agents require support in decision-making or problem-solving.

Peer Review MCP

An MCP tool set that enables AI agents to collaborate with other LLMs. The AI agent can request assistance or feedback from more capable models when it needs to evaluate its plans or when it gets stuck on a problem.

Tools

• ask-expert-for-peer-review

  • Ask an expert to peer review your plan. Provide the problem you are working on, and your detailed plan as well as any other context.
  • Input:
    • problem (string): The problem you are working on.
    • plan (string): The plan you have created.

• ask-expert-for-help

  • When confronting a challenging problem, seek guidance from an expert. Specify the problem and the issue you are having, as well as any other context.
  • Input:
    • problem (string): The problem you are trying to solve.
    • issue (string): The issue you are having.

Installation

Run the following commands in the root directory of the repository:

npm ci
npm run build

Then, add the following configuration to the MCP servers configuration file:

{
    "mcpServers": {
        "peer-review": {
            "command": "node",
            "args": [
                "/path/to/repo/dist/server.js"
            ],
            "env": {
                "HELPER_MODEL": "...",
                "HELPER_MODEL_API_KEY": "..."
            }
        }
    }
}

Replace /path/to/repo with the correct path.
Add the helper model (see list below) and the API key.

Make sure to restart the MCP client (e.g. Claude Desktop) for the changes to take effect.

For more information on how to configure the MCP server in Claude Dekstop, please refer to the MCP documentation for Claude Desktop Users

Supported Helper Models

Currently, the following models are supported as helper models:

• claude-3-7-sonnet-20250219 (Claude Sonnet 3.7)
• gemini-2.5-flash-preview-04-17 (Gemini 2.5 Flash)
• gemini-2.5-pro-preview-03-25 (Gemini 2.5 Pro)