mcp-server-cloudflare
by cloudflare
Overview
Enable Large Language Models (LLMs) to interact with and automate tasks across various Cloudflare services through a standardized Model Context Protocol (MCP).
Installation
No command providedEnvironment Variables
- OAUTH_KV
- MCP_COOKIE_ENCRYPTION_KEY
- ENVIRONMENT
- MCP_SERVER_NAME
- MCP_SERVER_VERSION
- CLOUDFLARE_CLIENT_ID
- CLOUDFLARE_CLIENT_SECRET
- MCP_OBJECT
- USER_DETAILS
- MCP_METRICS
- AI
- VECTORIZE
- AUTORAG_NAME
- WARP_DIAG_READER
- USER_CONTAINER
- CONTAINER_MANAGER
- USER_BLOCKLIST
Security Notes
The repository is a monorepo containing multiple distinct MCP servers, each leveraging Cloudflare services. Authentication is handled via Cloudflare OAuth or API tokens, with granular scopes defined per server to limit access. Sensitive credentials like `MCP_COOKIE_ENCRYPTION_KEY`, `CLOUDFLARE_CLIENT_ID`, and `CLOUDFLARE_CLIENT_SECRET` are expected to be provided via environment variables, not hardcoded. Logging and error tracking (via Sentry and Analytics Engine) are integrated for observability. A significant security consideration is the `apps/sandbox-container` server, which is explicitly designed to allow arbitrary code execution (`exec`) and file system operations within its environment. While this is its intended function as a sandbox, it introduces an inherent risk if not deployed and managed with robust isolation (e.g., secure containerization) and strict access controls. An LLM interacting with this tool could potentially be prompted to perform harmful actions within the sandboxed environment. The documentation indicates per-user Durable Object instances for containers and a user blocklist mechanism, which improves isolation and access control. However, the presence of direct `child_process.exec` calls in a server component requires careful consideration of the execution environment's isolation from the host system.
Similar Servers
mcp
Enables AI assistants to interact with Axiom's observability platform by exposing data and actions through the Model Context Protocol (MCP).
MyMCP
Dynamically convert any OpenAPI v3 specification into a fully-functional Model Context Protocol (MCP) server, exposing external APIs as MCP tools.
mold-inventory
An MCP server that provides an LLM with authenticated access to a mold inventory management API, allowing it to retrieve mold data on behalf of a user.
semantic-wake-intelligence-mcp
Provides a 3-layer temporal intelligence system for AI agents, managing context with causality tracking, memory management, and predictive pre-fetching via an MCP server.