Cloudflare MCP Server for OpenAI Agents SDK 25 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Cloudflare through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Cloudflare Assistant",
instructions=(
"You help users interact with Cloudflare. "
"You have access to 25 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Cloudflare"
)
print(result.final_output)
asyncio.run(main())
* 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:
The OpenAI Agents SDK auto-discovers all 25 tools from Cloudflare through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Cloudflare, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
- 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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Cloudflare MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 25 tools from Cloudflare
Why Use OpenAI Agents SDK with the Cloudflare MCP Server
OpenAI Agents SDK provides unique advantages when paired with Cloudflare through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Cloudflare + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Cloudflare MCP Server delivers measurable value.
Automated workflows: build agents that query Cloudflare, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Cloudflare, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Cloudflare tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Cloudflare to resolve tickets, look up records, and update statuses without human intervention
Cloudflare MCP Tools for OpenAI Agents SDK (25)
These 25 tools become available when you connect Cloudflare to OpenAI Agents SDK via MCP:
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
purge_cache
Use this after deploying content changes or updating static assets. Requires zone ID. Purge all cached content for a specific zone
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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Cloudflare immediately.
"List all serverless Cloudflare Workers deployed natively bound to my account."
"Query the KV namespace assigned to 'production_keys' and extract the specific text mapping 'gateway_url'."
"Check error statistics on my main D1 SQLite database instance over the last 24 hours."
Troubleshooting Cloudflare MCP Server with OpenAI Agents SDK
Common issues when connecting Cloudflare to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Cloudflare + OpenAI Agents SDK FAQ
Common questions about integrating Cloudflare MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
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Connect Cloudflare to OpenAI Agents SDK
Get your token, paste the configuration, and start using 25 tools in under 2 minutes. No API key management needed.