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performance-ai-mcp

performance-ai-mcp

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github.com/CSOAI-ORGOther0Updated 8w ago
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About performance-ai-mcp

performance-ai-mcp is an MCP server whose listed tools analyze waterfall data, suggest optimizations, and calculate Core Web Vitals. The README does not specify its intended audience or the performance domain covered.

Key features

  1. 01Analyze waterfall data
  2. 02Suggest optimizations
  3. 03Calculate Core Web Vitals

Use cases

  1. 01Analyze waterfall data
  2. 02Review optimization suggestions
  3. 03Calculate Core Web Vitals

MCP support

Exposes performance analysis tools to MCP clients. It can be configured with an MCP client using stdio transport.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "csoai-org-performance-ai": {
      "command": "uvx",
      "args": [
        "performance-ai-mcp"
      ]
    }
  }
}
Run commanduvx performance-ai-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypiperformance-ai-mcp1.0.8

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Scorecard: 86/100

Performance Ai MCP

MEOK AI Labs GSPC License PyPI

MEOK AI Labs MCP Server

MEOK AI Labs MCP Server

🚀 Quick Start

# Install via pip
pip install performance_ai_mcp

# Or install via Smithery
npx -y @smithery/cli@latest install performance-ai-mcp --client claude

✨ Features

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

📖 Documentation

🛡️ 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.

DomainPurpose
councilof.aiEU AI Act compliance marketplace
safetyof.aiAI safety & monitoring
meok.aiSovereign AI platform
cobolbridge.aiLegacy modernization

📜 License

MIT © CSOAI-ORG

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

MIT © [MEOK AI Labs](https://meok.ai)

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

💸 Try MEOK in 30 seconds — instant buy ladder

TierPriceWhat you getStripe
Smoke test£1Signed sample MCP-Hardening report + Article 50 PDFhttps://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j
Quick Kit£9EU AI Act Article 50 implementation guide (C2PA + EU-Icon)https://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j
Founder Call£2930-min 1-on-1 with the founderhttps://buy.stripe.com/5kQ6oJ0xS3ce8sl7ew8k91j

Refundable. UK Stripe — VAT-clean. Builds on the 81-MCP MEOK fleet. Verify any signed report at https://meok.ai/verify.

Configuration

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

{
  "mcpServers": {
    "performance-ai-mcp": {
      "command": "uvx",
      "args": ["performance-ai-mcp"]
    }
  }
}

Or: pip install performance-ai-mcp then run the performance-ai-mcp command (stdio transport).

Examples

Once configured, ask your assistant, for example:

  • "Use analyze_waterfall_data to …"
  • "Use suggest_optimizations to …"
  • "Use calculate_core_web_vitals to …"

Comments

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