Vector Knowledge Graph MCP

Vector Knowledge Graph MCP

mcp-name: io.github.CSOAI-ORG/vector-knowledge-graph-mcp

Vector Knowledge Graph

By MEOK AI Labs — MEOK AI Labs MCP Server

MEOK AI Labs MCP Server

MEOK AI Labs MCP Server

🚀 Quick Start

# Install via pip
pip install vector_knowledge_graph_mcp

# Or install via Smithery
npx -y @smithery/cli@latest install vector-knowledge-graph-mcp --client claude

✨ Features

• MCP protocol compliant
• Easy installation
• Well-documented API
• Production-ready
• Active maintenance

📖 Documentation

• Full Documentation
• API Reference
• EU AI Act Compliance Guide

🛡️ Compliance

This MCP server is built with EU AI Act compliance built-in:

• ✅ Article 9 — Risk Management System
• ✅ Article 13 — Transparency & Instructions for Use
• ✅ Article 15 — Bias Detection & Testing
• ✅ Article 26 — FRIA Support (where applicable)
• ✅ Article 50 — AI Content Watermarking (where applicable)

Need help getting compliant? Book a free 15-min diagnostic →

🏢 Enterprise

Need custom development, SLA guarantees, or white-label deployment?

• Pro: $99/mo — Full MCP suite + EU AI Act tracking
• Enterprise: $499/mo — Custom dev + SLA + Dedicated support

View Pricing → | Contact Sales →

🤝 Part of the MEOK Ecosystem

This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.

📜 License

MIT © CSOAI-ORG

_{Built with 💜 by MEOK AI Labs · UK Companies House 16939677}

License

MIT — MEOK AI Labs

Pairs with MEOK Governance Suite

Build something that touches users? You need compliance. MEOK ships 38 governance MCPs that drop in alongside this tool — EU AI Act, DORA, NIS2, CRA, GDPR, ISO 42001, FDA SaMD, MDR, Basel, MiFID II, MiCA, COPPA, and more.

# One-shot install of the governance pack
npx meok-setup --pack governance

Free tier: 10 calls/day per MCP. Pro tier (£79/mo): unlimited + cryptographically signed compliance attestations your auditor verifies independently.

→ Full catalogue: councilof.ai/catalogue→ MEOK AI Labs: meok.ai

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Configuration

Add to your claude_desktop_config.json (Claude Desktop) or your MCP client config:

{
  "mcpServers": {
    "vector-knowledge-graph-mcp": {
      "command": "uvx",
      "args": ["vector-knowledge-graph-mcp"]
    }
  }
}

Or: pip install vector-knowledge-graph-mcp then run the vector-knowledge-graph-mcp command (stdio transport).

Examples

Once configured, ask your assistant, for example:

• "Use add_node to …"
• "Use add_edge to …"
• "Use semantic_node_search to …"