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

Built by Vinkius GDPR 25 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Cloudflare as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Cloudflare. "
            "You have 25 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Cloudflare?"
    )
    print(response)

asyncio.run(main())
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* 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:

LlamaIndex agents combine Cloudflare tool responses with indexed documents for comprehensive, grounded answers. Connect 25 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.

  • 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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the Cloudflare MCP Server with LlamaIndex.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.py and run: python agent.py

04

Explore tools

The agent discovers 25 tools from Cloudflare

Why Use LlamaIndex with the Cloudflare MCP Server

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

01

Data-first architecture: LlamaIndex agents combine Cloudflare tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain Cloudflare tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query Cloudflare, a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what Cloudflare tools were called, what data was returned, and how it influenced the final answer

Cloudflare + LlamaIndex Use Cases

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

01

Hybrid search: combine Cloudflare real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query Cloudflare to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Cloudflare for fresh data

04

Analytical workflows: chain Cloudflare queries with LlamaIndex's data connectors to build multi-source analytical reports

Cloudflare MCP Tools for LlamaIndex (25)

These 25 tools become available when you connect Cloudflare to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Cloudflare + LlamaIndex FAQ

Common questions about integrating Cloudflare MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Cloudflare tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

Connect Cloudflare to LlamaIndex

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