MCP.Market

Multi-MCP server

by religa·io.github.religa/multi-mcp·v0.1.1·36 stars

Multi-model AI orchestration MCP server with code review, compare, and debate tools.

B83/100grade B
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Safety scan
B83/100

full report

Adoption
Growing

36 stars23 downloads/wk

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Multi-MCP tools (4)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • chat
  • codereview
  • models

    List available AI models. Returns model names, aliases, provider, and configuration.

  • version

    Get server version, configuration details, and list of available tools.

Public scan report

scanner v0.1.10 · 2026-10-01 · same rubric, same numbers if you re-run it

no findings
  • Code scan47 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 2 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 83/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Multi-MCP compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
83/100
higher than 68% of 4,460 AI and agents servers
Tools
4
the typical AI and agents server has 6
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
36
more than 91% of 2,711 AI and agents servers
Downloads a week
23
more than 9% of 1,538 AI and agents servers with a package

What its tools let an agent do: 4 read

Install Multi-MCP in Claude Code, Cursor or VS Code

claude mcp add multi-mcp -- uvx multi-mcp
Add to Cursor

What the publisher says

From the Multi-MCP repository's README, as published. We do not edit it. Read it on GitHub

Multi-MCP: Multi-Model Code Review and Analysis MCP Server for Claude Code

<!-- mcp-name: io.github.religa/multi-mcp -->

A multi-model AI orchestration MCP server for automated code review and LLM-powered analysis. Multi-MCP integrates with Claude Code CLI and OpenCode to orchestrate multiple AI models (OpenAI GPT, Anthropic Claude, Google Gemini) for code quality checks, security analysis (OWASP Top 10), and multi-agent consensus. Built on the Model Context Protocol (MCP), this tool enables Python developers and DevOps teams to automate code reviews with AI-powered insights directly in their development workflow.

Features

  • 🔍 Code Review - Systematic workflow with OWASP Top 10 security checks and performance analysis
  • 💬 Chat - Interactive development assistance with repository context awareness
  • 🔄 Compare - Parallel multi-model analysis for architectural decisions
  • 🎭 Debate - Multi-agent consensus workflow (independent answers + critique)
  • 🤖 Multi-Model Support - OpenAI GPT, Anthropic Claude, Google Gemini, and OpenRouter
  • 🖥️ CLI & API Models - Mix CLI-based (Gemini CLI, Codex CLI) and API models
  • 🏷️ Model Aliases - Use short names like mini, sonnet, gemini
  • 🧵 Threading - Maintain context across multi-step reviews

How It Works

Multi-MCP acts as an MCP server that Claude Code or OpenCode connects to, providing AI-powered code analysis tools:

  1. Install the MCP server and configure your AI model API keys
  2. Integrate with Claude Code or OpenCode automatically via make install
  3. Invoke tools using natural language (e.g., "multi codereview this file")
  4. Get Results from multiple AI models orchestrated in parallel

Performance

Fast Multi-Model Analysis:

  • ⚡ Parallel Execution - 3 models in ~10s (vs ~30s sequential)
  • 🔄 Async Architecture - Non-blocking Python asyncio
  • 💾 Conversation Threading - Maintains context across multi-step reviews
  • 📊 Low Latency - Response time = slowest model, not sum of all models

Quick Start

Prerequisites:

  • Python 3.11+
  • API key for at least one provider (OpenAI, Anthropic, Google, or OpenRouter)

Installation

<!-- Claude Code Plugin - Coming Soon

Option 1: Claude Code Plugin (Recommended)

# Add the marketplace
/plugin marketplace add religa/multi_mcp

# Install the plugin
/plugin install multi-mcp@multi_mcp

Then configure API keys in ~/.multi_mcp/.env (see Configuration). -->

Option 1: From Source

# Clone and install
git clone https://github.com/religa/multi_mcp.git
cd multi_mcp
# Execute ./scripts/install.sh
make install

# The installer will:
# 1. Install dependencies (uv sync)
# 2. Generate your .env file
# 3. Automatically add to Claude Code / OpenCode config (requires jq)
# 4. Test the installation

Option 2: Manual Configuration

If you prefer not to run make install:

# Install dependencies
uv sync

# Copy and configure .env
cp .env.example .env
# Edit .env with your API keys

Add to Claude Code (~/.claude.json) or OpenCode (~/.opencode/opencode.json), replacing /path/to/multi_mcp with your actual clone path:

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Multi-MCP: common questions

Is Multi-MCP server safe?
Mostly: it is graded B (83/100). Read the Multi-MCP safety report
How do I install Multi-MCP?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Multi-MCP need an API key?
Yes. The registry entry asks for OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, OPENROUTER_API_KEY.
Is Multi-MCP maintained?
The last commit was 35 days ago (2026-09-30). The latest release is v0.1.1.
What can I use instead of Multi-MCP?
Servers from other publishers that do the same job: PaperBanana MCP server, OpenWorkProof MCP server and three.ws Brain MCP server.
How does Multi-MCP compare with other AI and agents MCP servers?
safety score 83/100 (higher than 68% of 4,460 AI and agents servers); tools 4 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

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