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VegaMCP

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A production-grade MCP server providing an autonomous AI agent swarm, persistent semantic memory, browser automation, multi-model reasoning, and 78+ tools for A

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A production-grade MCP server providing an autonomous AI agent swarm, persistent semantic memory, browser automation, multi-model reasoning, and 78+ tools for AI-first testing and development.

README

🚀 VegaMCP v7.2

Full Spectrum Testing Edition — AI Agent Swarm Platform

FeaturesQuick StartConfiguration


VegaMCP is a production-grade MCP (Model Context Protocol) server providing an autonomous AI agent swarm, persistent semantic memory, browser automation, multi-model reasoning, security gateway, agent graphs, zero-trust identity, A2A protocol, Docker sandbox v5.0, AI-first testing suite (mobile, web, API, desktop, accessibility, security, visual), and 78+ tools — all accessible via any MCP-compatible client.

Version 7.2 (Sovereign Intelligence) introduces the production Claw Command Center, ultra-fast SQLite chat syncing, local vector Semantic Memory, LLM Output Evaluation, and 6 Unified Omni-Clusters.

📖 Complete Features

Read FEATURES.md for a comprehensive list of all 17 unified V7 capability clusters including Docker Sandbox v5.0.

Quick Start

Prerequisites

  • Node.js 20+
  • npm 9+

Installation

# Clone the repository
git clone https://github.com/Pastarafian/VegaMCP.git
cd VegaMCP

# Install dependencies
npm install

# Copy environment config
cp .env.example .env
# Edit .env with your API keys

# Build
npm run build

Connect to VS Code (Gemini / Copilot)

Create .vscode/mcp.json in your workspace:

{
  "servers": {
    "REDACTED": {
      "type": "stdio",
      "command": "node",
      "args": ["/path/to/VegaMCP/build/index.js"],
      "cwd": "/path/to/VegaMCP"
    }
  }
}

Note: API keys can be set in the env block of mcp.json or in the .env file (dotenv is loaded automatically).

Configuration

Copy .env.example to .env and configure:

# At least one reasoning model key required
OPENROUTER_API_KEY=          # Supports ALL models via OpenRouter
DEEPSEEK_API_KEY=            # Direct DeepSeek API (R1 + Chat)
KIMI_API_KEY=                # Kimi K2.5 for coding

# Optional integrations
GITHUB_TOKEN=                # GitHub API (60→5000 req/hr)
TAVILY_API_KEY=              # AI-powered web search
SEARXNG_URL=                 # Self-hosted search fallback
SENTRY_AUTH_TOKEN=           # Error tracking
SENTRY_ORG=
SENTRY_PROJECT=

# Budget controls
TOKEN_DAILY_BUDGET_USD=5.00
TOKEN_HOURLY_BUDGET_USD=1.00

# Tool profiles
VEGAMCP_TOOL_PROFILE=full    # full | minimal | research | coding | ops

Project Structure

VegaMCP/
├── src/
│   ├── index.ts                     # Server entry point + hub router
│   ├── mcp-extensions.ts            # Sampling, logging, progress, roots
│   ├── mcp-protocol/               # v6.0 / v7.0 protocol modules
│   ├── db/                          # SQLite + vector store
│   ├── swarm/                       # Agent swarm (10 agents)
│   ├── tools/                       # All tool implementations
│   ├── resources/                   # MCP resource providers
│   ├── prompts/                     # MCP prompt templates
│   └── security/                    # Rate limiter, validator, guard
├── .env.example                     # Environment template
├── package.json
└── tsconfig.json

License

MIT


Built with TypeScript • MCP SDK • sql.js • Playwright • DeepSeek • A2A Protocol

from github.com/Pastarafian/VegaMCP

Installing VegaMCP

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/Pastarafian/VegaMCP

FAQ

Is VegaMCP MCP free?

Yes, VegaMCP MCP is free — one-click install via Unyly at no cost.

Does VegaMCP need an API key?

No, VegaMCP runs without API keys or environment variables.

Is VegaMCP hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install VegaMCP in Claude Desktop, Claude Code or Cursor?

Open VegaMCP on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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