SLA.directory MCP server

An MCP server that lets AI assistants query SLA.directory in context: uptime commitments, service credits, claim windows, and per-service SLAs for cloud and SaaS vendors.

It reads the public SLA.directory API at runtime (with a short cache). No API key, no data bundled.

Tools

• search_vendors(query): find vendors and services by name or category.

• get_vendor(slug): full SLA record for one vendor.

• get_service_sla(slug, service?): per-service SLAs (e.g. AWS S3 vs EC2), optionally filtered.

• compare_vendors(slugs[]): key terms side by side (uptime, max credit, claim window, auto-credit).

• list_categories() and vendors_in_category(category).

Vendor lookups are fuzzy (e.g. "Amazon Web Services" resolves to aws), answers are concise and cited (every result carries the official source URL and verification date), and tools are marked read-only so assistants can call them freely.

Related MCP server: GetMonitor MCP Server

Prompts

Ready-made flows you can pick in the client:

• sla_review(vendor): summarize one vendor's SLA (uptime, credits, claim process, exclusions, weakest services).

• compare_for_renewal(vendors): compare several vendors for a renewal decision.

• weakest_services(vendor): find a vendor's lowest-uptime services for error-budget planning.

Use it

Run with Node 18+ (no install needed once published):

npx sla-directory-mcp

Claude Desktop / Cursor

Add to your MCP config:

{
  "mcpServers": {
    "sla-directory": {
      "command": "npx",
      "args": ["-y", "sla-directory-mcp"]
    }
  }
}

Then ask things like "What's AWS S3's SLA?", "Compare Stripe, Adyen, and PayPal SLA credits", or "Which security vendors offer automatic credits?"

Run from source

npm install
npm run build
node dist/index.js     # stdio server

Point it at a different API base with SLA_API_BASE (defaults to https://sla.directory/api/v1).

License

MIT. SLA data served by the API is licensed CC-BY-4.0 by SLA.directory. Always confirm against the vendor's official SLA before relying on this data for contractual or financial decisions.