MCP Servers for Global Edge Performance.
Cache hit ratios monitored, edge latency tracked, WAF threats counted, performance reports delivered , run your edge infrastructure from one prompt
Works with every AI agent you already use
…and any MCP-compatible client
Waiting for input…
Gemini How It Works
Your AI agent reads Cloudflare zone analytics for your 4 domains: api.example.com, app.example.com, docs.example.com, cdn.example.com. Cache hit ratio for cdn.example.com is 94.2% , healthy.
But api.example.com dropped to 61.3% from yesterday's 87.1%. That is a 26-point drop. The agent checks Workers analytics , the edge function handling `/api/search` has a p99 of 890ms, up from 320ms.
Something changed. It pulls the Grafana dashboard for the origin server: CPU is at 78%, response time is 450ms , the origin is fine.
The problem is at the edge. WAF blocked 1,247 requests in the last 24 hours , 89% from 3 IP ranges.
Normal DDoS mitigation. It posts to #platform-ops: 'Edge Report , June 3, 2026. api.example.com cache hit ratio dropped 26 points (87% 61%).
Worker `/api/search` p99 at 890ms (was 320ms). Origin healthy. Investigate Worker deployment. WAF: 1,247 blocks, no anomalies. All other zones nominal.'
MCP Server Orchestration: 3 MCP Servers, one intelligent agent
Connect Cloudflare, Grafana and Discord MCP servers so your AI agent monitors your edge infrastructure health, pulls cache performance and WAF threat data from Cloudflare, correlates it with Grafana dashboards for origin server metrics, and delivers a daily ops report to your Discord channel. Platform engineers managing CDN, Workers and security rules across multiple domains get a single-pane ops view without opening three dashboards. One prompt and your edge is in focus.
Cloudflare
triggerReads zone analytics, cache ratios, Workers performance and WAF events
get_zone_analytics get_worker_analytics list_zones list_workers purge_cache Grafana
actionPulls origin server dashboards and alert states
get_dashboard search_dashboards firing_alerts list_datasources Discord
actionPosts daily edge ops reports and threat alerts
create_message list_guild_channels Run This Automation Today
Connect Claude, ChatGPT, Cursor, or any AI agent to the Vinkius catalog and run this automation in minutes.
Build Your Own MCP
Turn any internal API into an MCP server. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Connect & Automate
The 3 servers this recipe uses are ready in the catalog. Connect them once, paste a prompt, and your AI runs the full workflow.
- Cloudflare, Grafana & Discord ready in the catalog right now
- Add more from 4,700+ servers whenever you need
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers and recipes added every week
Superpowers you didn't know your AI had
The Vinkius catalog gives your agent access to 4,700+ MCP servers and the intelligence to combine them. Imagine never logging into another dashboard. Your AI handles the work across every tool, in one conversation. That's what this infrastructure was built for.
Cross-Platform Intelligence
Your agent doesn't just connect to tools. It understands the relationships between them. Data flows where it needs to go, automatically, with full context preserved across every platform.
Contextual Reasoning
Every decision your agent makes considers the full picture. It reads CRM data, checks calendars, reviews conversation history, and acts on everything at once. Not step by step. All at once.
Productivity at Scale
What used to take 45 minutes across five different dashboards now takes one sentence. Your agent runs the entire workflow end to end while you focus on decisions that actually matter.
Zero-Config Reliability
No API keys to paste. No webhooks to configure. No YAML to debug. Connect your MCP servers once, and your agent handles the rest. Every time, without intervention.
Made for
exactly this
Your AI agent taps into the entire Vinkius MCP catalog to handle these for you. You describe what you need. It does the rest.
Platform engineers managing Cloudflare CDN, Workers and WAF across multiple domains who need a daily edge health summary
DevOps teams who want automated alerting when cache hit ratios drop or Worker latency spikes beyond acceptable thresholds
Security engineers who need a daily WAF threat digest with attack pattern classification without manually reviewing Cloudflare logs
SRE teams running Grafana for origin monitoring who want correlated edge-and-origin performance data in a single view
Frequently Asked Questions About This MCP Server Orchestration
Which MCP servers do I need for this workflow?
Three: Cloudflare, Grafana and Discord. Connect all three to your AI client before running any prompt from this page.
Does this work with Claude Desktop, Cursor or Windsurf?
Yes. Any AI client that supports the Model Context Protocol works , Claude Desktop, Cursor, Windsurf, Cline and others.
Can I trigger a cache purge from this workflow?
Yes. The Cloudflare MCP server includes a purge_cache tool. Ask the agent to purge a specific zone or URL pattern.
What if I do not use Grafana?
You can run this with just Cloudflare and Discord. The Grafana component adds origin correlation but is optional for edge-only monitoring.
How does it handle multiple Cloudflare accounts?
The agent reads all zones accessible by your API token. If you have zones across accounts, ensure your token has the right permissions.
Can I customize the alert thresholds?
Yes. Tell the agent in your prompt: 'Alert if cache hit ratio drops below 80% or Worker p99 exceeds 500ms.' The agent adapts to your thresholds.
Detect Infrastructure Drift Early Using MCP
Someone clicked 'apply' in the Cloudflare dashboard and your Terraform state no longer matches reality , your agent finds the drift
MCP Servers to Find Your Most Expensive APIs
API traffic metered, cache savings calculated, origin load measured, cost projections generated , optimize your API infrastructure costs with data
MCP Recipe for Full-Stack Observability
Two monitoring tools, zero correlation , your Datadog alerts say 'high latency' and your Grafana dashboards say 'database connections maxed' but nobody connected the dots until the postmortem
Catch Frontend Downtime Early Using MCP Servers
Your landing page passed the Lighthouse audit but your checkout flow takes 11 seconds in Brazil because nobody runs synthetic checks from outside us-east-1
Debug CI Pipeline Failures Faster Using MCP
Your CI pipeline takes 47 minutes and nobody knows which step is the bottleneck , your AI agent analyzes every build, identifies the slow steps, and posts a weekly efficiency report
Get Instant Incident Alerts in Discord via MCP
Monitors fire, Discord gets the alert, the incident log updates itself , no human in the loop
MCP servers used in this workflow
Cloudflare
Cloudflare MCP Server manages your entire edge infrastructure via AI agents. Use it to deploy Workers, manage secrets, query D1 databases, and monitor traffic across KV, R2, and CDN—all from natural language commands.
Grafana
Grafana MCP Server gives your AI agent full control over your observability stack. Use it to search dashboards by tag or title, inspect precise PromQL, LogQL, or SQL queries, list all connected data sources (Prometheus, Loki, CloudWatch, SQL), and monitor live alert states—all from a single chat interface.
Discord
Discord MCP Server gives your AI agent full control over Discord communities. You can list channels, manage members, send messages with Markdown, and run moderation commands—all without leaving your chat client. It lets your agent read channel history, audit server metadata, and delete messages or channels instantly.