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Vinkius

Cloudflare MCP Server for Mastra AI 25 tools — connect in under 2 minutes

Built by Vinkius GDPR 25 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Cloudflare through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.

Vinkius supports streamable HTTP and SSE.

typescript
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";

async function main() {
  // Your Vinkius token — get it at cloud.vinkius.com
  const mcpClient = await createMCPClient({
    servers: {
      "cloudflare": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Cloudflare Agent",
    instructions:
      "You help users interact with Cloudflare " +
      "using 25 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Cloudflare?"
  );
  console.log(result.text);
}

main();
Cloudflare
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Cloudflare MCP Server

What you can do

Connect AI agents to Cloudflare's platform for comprehensive edge infrastructure management:

Mastra's agent abstraction provides a clean separation between LLM logic and Cloudflare tool infrastructure. Connect 25 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.

  • Manage Workers — list, inspect, delete serverless functions across your account
  • Control deployments — version history, immediate/gradual rollouts, rollback capabilities
  • Manage secrets — create, list, and delete encrypted environment secrets securely
  • Configure routes — URL patterns that trigger Workers at specific paths or domains
  • Query KV storage — read/write key-value pairs from Workers KV namespaces
  • Execute D1 queries — run SQL queries against Cloudflare's serverless SQLite databases
  • Inspect R2 buckets — list and manage object storage buckets
  • Monitor analytics — zone traffic, Worker invocations, CPU usage, and error rates
  • Tail Worker logs — create real-time logging sessions for debugging in production
  • Purge CDN cache — clear cached content to serve fresh origin data

The Cloudflare MCP Server exposes 25 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Cloudflare to Mastra AI via MCP

Follow these steps to integrate the Cloudflare MCP Server with Mastra AI.

01

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

Mastra discovers 25 tools from Cloudflare via MCP

Why Use Mastra AI with the Cloudflare MCP Server

Mastra AI provides unique advantages when paired with Cloudflare through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Cloudflare without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every Cloudflare tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure

Cloudflare + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the Cloudflare MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query Cloudflare, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed Cloudflare as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query Cloudflare on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using Cloudflare tools alongside other MCP servers

Cloudflare MCP Tools for Mastra AI (25)

These 25 tools become available when you connect Cloudflare to Mastra AI via MCP:

01

create_deployment

Strategy can be immediate (100% traffic immediately) or gradual (percentage-based rollout). Requires script name, version ID, and deployment strategy. Use this to roll out new features, rollback to previous versions, or perform canary deployments. Deploy a specific Worker version to traffic

02

create_secret

Secrets are encrypted at rest and injected at runtime. Requires script name, secret name, and secret value. Common use: API keys, database passwords, OAuth tokens. The secret becomes available via env.VARIABLE_NAME in your Worker code. Create or update a secret for a Cloudflare Worker

03

create_tail_session

log() output and exceptions. Returns a tail ID and WebSocket URL for streaming logs. Use this for debugging Workers in production or monitoring error output. Create a tail logging session for a Cloudflare Worker

04

create_worker_route

Requires zone ID, URL pattern (e.g., "example.com/api/*"), and script name. Use this to expose your Worker at specific URL paths or domains. Create a new route pattern for a Cloudflare Worker

05

delete_secret

Use this to clean up unused secrets or rotate credentials. Requires script name and secret name. After deletion, the Worker will no longer have access to the secret value. Delete a secret from a Cloudflare Worker

06

delete_tail_session

Requires script name and tail ID. Use this to clean up unused tail sessions when debugging is complete. Delete a tail logging session for a Cloudflare Worker

07

delete_worker

This action cannot be undone. Requires the script name. Confirm with the user before proceeding. Delete a Cloudflare Worker script and all its associated resources

08

delete_worker_route

Use this to stop serving a Worker at specific URLs. Requires zone ID and route ID. Delete a route pattern from a Cloudflare Worker

09

get_kv_key

Returns the raw value as JSON. Use this to read configuration values, cached responses, or user data stored in KV. Get the value of a specific key in a KV namespace

10

get_worker

Requires the script name from list_workers results. Use this to review Worker configuration before making updates or debugging. Get detailed information about a specific Cloudflare Worker

11

get_worker_analytics

Returns data for recent invocations. Use this to monitor Worker performance, identify errors, or track usage trends. Get analytics data for a specific Cloudflare Worker

12

get_worker_version

Requires script name and version ID from list_worker_versions results. Use this to audit version contents or prepare for rollback deployment. Get detailed information about a specific Worker version

13

get_zone_analytics

Returns aggregated data for the last 24 hours. Use this to monitor traffic patterns, identify spikes, or measure CDN performance. Get analytics data for a specific Cloudflare zone

14

list_d1_databases

Returns database IDs, names, creation dates, and file sizes. Use this to identify available databases before querying. List all D1 databases in your Cloudflare account

15

list_deployments

Returns deployment IDs, version IDs, strategies (immediate, gradual), creation dates, and traffic percentages. Use this to review current deployment state, monitor gradual rollouts, or identify which version is live. List all deployments for a specific Cloudflare Worker

16

list_kv_keys

Returns key names, expiration metadata, and sizes. Use this to audit stored data or find specific keys before reading values. List all keys in a specific KV namespace

17

list_kv_namespaces

KV namespaces are key-value stores for Workers. Returns namespace IDs, titles, and creation dates. Use this to identify which namespaces exist before reading/writing data. List all KV namespaces in your Cloudflare account

18

list_r2_buckets

Returns bucket names, creation dates, and storage locations. Use this to identify available storage buckets before managing objects. List all R2 storage buckets in your Cloudflare account

19

list_secrets

Returns secret names and types (secret_text, secret_key). Secret values are never returned for security. Use this to audit which secrets are configured before adding new ones or cleaning up unused secrets. List all secrets for a specific Cloudflare Worker

20

list_worker_routes

Returns route patterns, associated script names, and zone IDs. Use this to understand which URLs invoke your Worker before adding or removing routes. List all route patterns associated with a Cloudflare Worker

21

list_worker_versions

Each version represents a deployed code snapshot with unique ID, creation date, and metadata. Returns version IDs, timestamps, and author information. Use this to review deployment history, rollback to previous versions, or audit code changes. List all versions of a specific Cloudflare Worker

22

list_workers

Returns script names, creation dates, modification dates, and deployment status. Use this as the first step to identify which Workers exist before managing versions, deployments, or secrets. List all Cloudflare Workers scripts in your account

23

list_zones

Returns zone IDs, domain names, status, plan, and name servers. Use this to identify zone IDs needed for Worker routes, DNS management, or cache operations. List all DNS zones in your Cloudflare account

24

purge_cache

Use this after deploying content changes or updating static assets. Requires zone ID. Purge all cached content for a specific zone

25

query_d1

Supports SELECT, INSERT, UPDATE, DELETE operations. Returns query results as JSON. Use this for data analysis, migrations, or ad-hoc queries. Requires database ID and SQL query string. Execute a SQL query against a D1 database

Example Prompts for Cloudflare in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with Cloudflare immediately.

01

"List all serverless Cloudflare Workers deployed natively bound to my account."

02

"Query the KV namespace assigned to 'production_keys' and extract the specific text mapping 'gateway_url'."

03

"Check error statistics on my main D1 SQLite database instance over the last 24 hours."

Troubleshooting Cloudflare MCP Server with Mastra AI

Common issues when connecting Cloudflare to Mastra AI through the Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

Cloudflare + Mastra AI FAQ

Common questions about integrating Cloudflare MCP Server with Mastra AI.

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.

Connect Cloudflare to Mastra AI

Get your token, paste the configuration, and start using 25 tools in under 2 minutes. No API key management needed.