{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm-cloudflare-mcp-server-cloudflare","slug":"cloudflare-mcp-server-cloudflare","name":"@cloudflare/mcp-server-cloudflare","type":"mcp","url":"https://github.com/cloudflare/mcp-server-cloudflare","page_url":"https://unfragile.ai/cloudflare-mcp-server-cloudflare","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm-cloudflare-mcp-server-cloudflare__cap_0","uri":"capability://tool.use.integration.mcp.protocol.server.with.http.streaming.transport","name":"mcp protocol server with http streaming transport","description":"Implements the Model Context Protocol (MCP) specification as a production-grade server deployed on Cloudflare Workers, using HTTP streaming via /mcp endpoint with streamble-http transport for bidirectional communication between LLMs and Cloudflare services. Handles tool discovery, prompt templates, and resource management through standardized MCP message framing with automatic serialization/deserialization of tool schemas and responses.","intents":["I need to expose Cloudflare APIs to Claude, ChatGPT, or other LLM clients using a standard protocol","I want my LLM to discover available tools and their schemas automatically without manual configuration","I need reliable streaming responses from Cloudflare operations without polling or webhooks"],"best_for":["AI agent developers building LLM-powered infrastructure management tools","Teams integrating Cloudflare services into AI-native workflows","Enterprises requiring standardized LLM-to-API gateway patterns"],"limitations":["Legacy SSE transport (/sse endpoint) is deprecated; HTTP streaming is primary transport","Each MCP server instance is stateless — requires external state management for multi-step workflows","Tool execution latency includes Cloudflare Worker cold-start overhead (~50-200ms on first invocation)"],"requires":["Cloudflare account with Workers enabled","MCP client library compatible with HTTP streaming transport (e.g., Claude SDK, Anthropic SDK)","API token or OAuth 2.0 credentials for Cloudflare authentication"],"input_types":["MCP tool call requests (JSON with tool name, arguments)","MCP prompt requests (template names with variables)","MCP resource requests (URIs for data access)"],"output_types":["MCP tool results (JSON-serialized responses)","MCP prompt completions (rendered templates)","MCP resource data (structured or unstructured)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_1","uri":"capability://safety.moderation.oauth.2.0.and.api.token.dual.mode.authentication","name":"oauth 2.0 and api token dual-mode authentication","description":"Provides two authentication pathways: OAuth 2.0 flow for user-based access (interactive authorization with Cloudflare account) and API token mode for programmatic access (service-to-service authentication). Implements secure credential validation, token refresh, and user state management through Durable Objects for session persistence, with automatic credential injection into downstream Cloudflare API calls.","intents":["I need to authenticate LLM clients with my Cloudflare account without exposing raw API tokens","I want to support both interactive (OAuth) and programmatic (token-based) access patterns","I need to track which user/service made which API calls for audit and rate-limiting purposes"],"best_for":["Multi-tenant SaaS platforms exposing Cloudflare APIs to end users","Enterprise teams with strict credential management policies","Developers building both interactive and automated workflows"],"limitations":["OAuth flow requires user interaction — not suitable for fully automated, headless scenarios","API token mode has no built-in rotation; tokens must be manually rotated and revoked","Durable Objects state storage has eventual consistency guarantees; immediate token revocation may have ~1-5s propagation delay"],"requires":["Cloudflare OAuth application registered in Cloudflare dashboard","Cloudflare API token with appropriate scopes (for token-based auth)","Durable Objects binding in Worker configuration for session state"],"input_types":["OAuth authorization code (from user redirect)","API token string (Bearer token format)","User credentials (email/password for interactive flows)"],"output_types":["Access token (JWT or opaque token)","Refresh token (for OAuth flows)","User context object (email, account ID, permissions)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_10","uri":"capability://search.retrieval.documentation.search.and.semantic.code.lookup","name":"documentation search and semantic code lookup","description":"Implements a specialized MCP server for searching Cloudflare documentation and code examples using semantic search powered by Vectorize embeddings. Enables LLMs to find relevant documentation sections, API examples, and best practices based on natural language queries, with support for filtering by documentation category (Workers, Pages, API, etc.) and code language.","intents":["I want to find the right Cloudflare API or feature to solve a user's problem","I need to retrieve code examples for a specific Cloudflare service","I want to understand best practices and common patterns for a Cloudflare feature"],"best_for":["LLM-powered developer assistants and support chatbots","Teams building Cloudflare-focused AI applications","Developers learning Cloudflare APIs through semantic search"],"limitations":["Documentation search quality depends on embedding model; technical jargon may not match user queries","Documentation is static; real-time API changes may not be reflected immediately","Code examples are limited to official Cloudflare documentation; community examples are not indexed"],"requires":["Cloudflare documentation indexed in Vectorize","Embedding model for semantic search","Category metadata for filtering results"],"input_types":["Natural language query (e.g., 'How do I cache API responses?')","Documentation category filter (Workers, Pages, API, etc.)","Code language preference (JavaScript, Python, Go, etc.)","Search scope (all docs, specific product, specific version)"],"output_types":["Documentation sections (title, URL, excerpt, relevance score)","Code examples (language, snippet, context)","Related topics (linked documentation, related APIs)","Metadata (last updated, product version, difficulty level)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_11","uri":"capability://image.visual.browser.rendering.and.screenshot.capture","name":"browser rendering and screenshot capture","description":"Exposes Cloudflare Browser Rendering capabilities through MCP tools for rendering web pages, capturing screenshots, and extracting page content. Implements headless browser automation with support for JavaScript execution, form interaction, and dynamic content rendering, providing LLMs with the ability to analyze visual content and interact with web applications.","intents":["I want to take a screenshot of a web page to analyze its visual layout","I need to extract text and structured data from a dynamically-rendered page","I want to interact with a web form or JavaScript-heavy application"],"best_for":["Web scraping and content extraction tasks","Visual analysis and screenshot-based testing","Automation of web application interactions"],"limitations":["Browser rendering has high latency (~2-10 seconds per page); not suitable for real-time interactions","JavaScript execution is limited to 30 seconds; complex rendering may timeout","Screenshot quality and size are limited; high-resolution captures may exceed token budgets"],"requires":["Cloudflare Browser Rendering service enabled","Target URL or HTML content","Optional: JavaScript code to execute before rendering"],"input_types":["URL or HTML content","Viewport size (width, height)","JavaScript to execute (optional)","Wait conditions (selector, timeout)","Form data for interaction"],"output_types":["Screenshot (PNG or JPEG image)","Page content (HTML, text, structured data)","Rendered DOM (for analysis)","Performance metrics (load time, resource count)"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_12","uri":"capability://automation.workflow.shared.mcp.infrastructure.and.observability.framework","name":"shared mcp infrastructure and observability framework","description":"Provides shared packages (@repo/mcp-common, @repo/mcp-observability, @repo/eval-tools) that all MCP servers depend on for authentication, metrics collection, and testing. Implements centralized observability through structured logging, distributed tracing, and metrics aggregation, with support for monitoring tool execution latency, error rates, and authentication failures across all servers.","intents":["I want to monitor the health and performance of all MCP servers from a single dashboard","I need to debug issues across multiple MCP servers without accessing each one individually","I want to understand which tools are most frequently used and which have the highest latency"],"best_for":["Platform teams managing multiple MCP servers","DevOps engineers monitoring production MCP deployments","Teams building observability and debugging tools"],"limitations":["Metrics aggregation has ~1-5 minute latency; real-time monitoring requires custom dashboards","Distributed tracing adds ~5-10% overhead to tool execution; high-volume deployments may see performance impact","Log volume limits apply per Worker; high-traffic servers may have truncated logs"],"requires":["Cloudflare Workers with observability enabled","Metrics backend (Prometheus, Datadog, etc.) for aggregation","Distributed tracing setup (optional, for detailed debugging)"],"input_types":["Metrics queries (tool name, time range, aggregation)","Log filters (error level, server, time range)","Trace context (request ID, user ID)"],"output_types":["Metrics (latency percentiles, error rates, request counts)","Logs (structured entries with context)","Traces (request flow across servers)","Alerts (anomalies, errors, performance degradation)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_13","uri":"capability://automation.workflow.monorepo.development.framework.with.pnpm.workspaces.and.turbo","name":"monorepo development framework with pnpm workspaces and turbo","description":"Implements a production monorepo structure using pnpm workspaces for dependency management and Turbo for build orchestration, enabling efficient development and deployment of 15+ independent MCP servers. Provides shared build configuration, testing infrastructure (Vitest), and deployment pipelines that reduce duplication and ensure consistency across all servers.","intents":["I want to add a new MCP server without duplicating build and deployment configuration","I need to run tests across all servers efficiently without rebuilding unchanged code","I want to deploy multiple servers simultaneously while respecting dependency order"],"best_for":["Teams building multiple MCP servers with shared infrastructure","Organizations requiring consistent development practices across services","DevOps teams managing complex deployment pipelines"],"limitations":["Monorepo complexity increases as the number of servers grows; dependency management becomes harder","Turbo caching requires careful configuration; incorrect cache keys can lead to stale builds","pnpm workspace hoisting can cause version conflicts if not carefully managed"],"requires":["pnpm 8.0+ for workspace management","Turbo 1.0+ for build orchestration","Node.js 18+ for development"],"input_types":["New MCP server template (scaffolding)","Build configuration (tsconfig, eslint, prettier)","Deployment manifest (wrangler.jsonc)"],"output_types":["Built artifacts (compiled JavaScript, type definitions)","Test results (coverage, pass/fail)","Deployment status (per-server, per-region)"],"categories":["automation-workflow","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_2","uri":"capability://tool.use.integration.multi.server.tool.registry.with.schema.based.function.calling","name":"multi-server tool registry with schema-based function calling","description":"Maintains a centralized registry of 100+ tools across 15+ specialized MCP servers (Workers Observability, DNS Analytics, AI Gateway, etc.), each with JSON Schema definitions for parameters and return types. Implements automatic tool discovery, schema validation, and routing to the appropriate server based on tool namespace, with support for tool categorization (Common Tools, Container Management, Observability, Workers Management, AI & Data Tools).","intents":["I want my LLM to discover all available Cloudflare operations without hardcoding tool definitions","I need the LLM to understand parameter requirements and return types before calling a tool","I want to organize tools by domain (DNS, Workers, AI Gateway) so the LLM can find relevant operations"],"best_for":["AI agents that need to dynamically discover and invoke Cloudflare operations","LLM applications requiring schema-driven function calling with validation","Teams building multi-domain automation (e.g., DNS + Workers + AI Gateway in one workflow)"],"limitations":["Schema validation adds ~50-100ms per tool invocation for complex nested schemas","Tool registry is static per deployment; adding new tools requires redeployment of the MCP server","No built-in tool versioning — breaking changes to tool signatures require client-side updates"],"requires":["JSON Schema definitions for all tools (auto-generated from TypeScript interfaces)","Tool namespace prefixes (e.g., 'workers-observability:', 'dns-analytics:') for routing","MCP client with schema-based function calling support (e.g., OpenAI Functions API)"],"input_types":["Tool name (string with namespace prefix)","Tool arguments (JSON object matching schema)","Optional: parameter overrides or context hints"],"output_types":["Tool result (JSON, structured data, or text)","Error response with validation details","Tool metadata (description, parameters, examples)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_3","uri":"capability://data.processing.analysis.workers.observability.tool.suite.with.real.time.metrics.and.logs","name":"workers observability tool suite with real-time metrics and logs","description":"Exposes Cloudflare Workers runtime observability through MCP tools that query Analytics Engine, tail real-time logs, retrieve error traces, and analyze performance metrics. Implements direct integration with Cloudflare's Analytics Engine for structured query execution and Durable Objects for log streaming, providing LLMs with visibility into Worker execution, CPU time, memory usage, and request/error patterns.","intents":["I need to debug a failing Worker by querying its logs and error traces through an LLM interface","I want to analyze Worker performance metrics (CPU, memory, request latency) to identify bottlenecks","I need to stream real-time logs from a Worker to understand what's happening during execution"],"best_for":["Developers debugging Cloudflare Workers using AI-assisted troubleshooting","DevOps teams building LLM-powered observability dashboards","Teams analyzing Worker performance trends and anomalies"],"limitations":["Real-time log streaming is limited to 30 seconds of tail data; historical logs require Analytics Engine queries","Analytics Engine queries have ~5-10 minute data latency; real-time metrics are not available","Log volume limits apply per Worker; high-traffic Workers may have truncated log history"],"requires":["Cloudflare Workers with Analytics Engine enabled","Appropriate API permissions for reading logs and metrics","Durable Objects binding for log streaming capability"],"input_types":["Worker script name or ID","Time range for log queries (start/end timestamps)","Filter criteria (error level, request path, etc.)","Metric type (cpu_time, memory, request_count, etc.)"],"output_types":["Structured log entries (timestamp, level, message, context)","Aggregated metrics (min/max/avg/p95/p99 values)","Error traces with stack information","Performance timeline (request duration breakdown)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_4","uri":"capability://data.processing.analysis.dns.analytics.and.query.pattern.analysis","name":"dns analytics and query pattern analysis","description":"Provides MCP tools for querying DNS analytics data through Cloudflare's Analytics Engine, enabling LLMs to analyze query patterns, identify top domains, detect DNS anomalies, and retrieve DNSSEC validation metrics. Implements time-series aggregation queries with configurable granularity (1m, 5m, 1h, 1d) and supports filtering by query type, response code, and geographic origin.","intents":["I want to understand DNS query patterns for my domain to optimize caching and routing","I need to identify suspicious DNS activity or anomalies that might indicate attacks","I want to analyze which domains are most queried and from which regions"],"best_for":["Security teams investigating DNS-based attacks or anomalies","DevOps engineers optimizing DNS performance and caching","Network administrators analyzing traffic patterns across zones"],"limitations":["Analytics data has ~5-10 minute latency; real-time DNS queries are not available","Query granularity is limited to 1-minute intervals; sub-minute analysis requires raw log access","Aggregation queries are limited to 7-day windows; longer historical analysis requires multiple queries"],"requires":["Cloudflare zone with DNS analytics enabled","API permissions for reading DNS analytics","Analytics Engine access for the zone"],"input_types":["Zone name or ID","Time range (start/end timestamps)","Aggregation granularity (1m, 5m, 1h, 1d)","Filter criteria (query type, response code, country, etc.)"],"output_types":["Time-series data (timestamp, query count, response codes)","Top N domains/countries (ranked by query volume)","Anomaly scores or statistical summaries","DNSSEC validation metrics"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_5","uri":"capability://tool.use.integration.ai.gateway.tool.integration.and.model.routing","name":"ai gateway tool integration and model routing","description":"Exposes Cloudflare AI Gateway capabilities through MCP tools, enabling LLMs to configure model routing policies, analyze gateway metrics, and manage rate limiting rules. Implements schema-based configuration for routing strategies (load balancing, failover, A/B testing) and provides visibility into gateway performance, cache hit rates, and model availability across multiple LLM providers.","intents":["I want to configure intelligent routing between multiple LLM providers (OpenAI, Anthropic, etc.) based on cost or latency","I need to set up rate limiting and caching policies for my AI Gateway","I want to analyze which models are being used most and optimize costs"],"best_for":["Teams managing multi-provider LLM deployments","Cost-conscious organizations optimizing LLM spending","Developers building resilient AI applications with failover"],"limitations":["Routing policy changes take ~30-60 seconds to propagate globally","Rate limiting is enforced at the gateway level; per-user limits require additional application logic","Cache hit rates are aggregated; per-endpoint cache analysis requires custom queries"],"requires":["Cloudflare AI Gateway account with multiple provider integrations","API keys for target LLM providers (OpenAI, Anthropic, etc.)","Appropriate API permissions for gateway configuration"],"input_types":["Routing policy definition (provider weights, failover order)","Rate limit configuration (requests/minute, tokens/hour)","Cache policy (TTL, key patterns)","Model selection criteria (cost, latency, availability)"],"output_types":["Routing configuration (applied policy, provider weights)","Gateway metrics (requests, cache hits, latency percentiles)","Cost analysis (per-provider spending, token usage)","Availability status (provider health, failover events)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_6","uri":"capability://automation.workflow.workers.builds.and.deployment.management","name":"workers builds and deployment management","description":"Exposes Cloudflare Workers deployment pipeline through MCP tools for triggering builds, monitoring deployment status, retrieving build logs, and managing deployment rollbacks. Implements integration with Cloudflare's build system to track compilation status, asset bundling, and deployment propagation across the global edge network, with support for preview deployments and production rollouts.","intents":["I want to deploy a Worker update and monitor its rollout across regions","I need to check if a build succeeded and retrieve compilation errors","I want to rollback a broken deployment to the previous version"],"best_for":["DevOps teams automating Worker deployments through LLM agents","Developers debugging build failures with AI assistance","Teams implementing CI/CD pipelines with LLM-driven decision making"],"limitations":["Build compilation time varies (30s-5m) depending on Worker complexity; LLM must wait for completion","Deployment propagation to all edge locations takes ~2-5 minutes; immediate global availability is not guaranteed","Rollback is limited to the previous 10 deployments; older versions require manual recovery"],"requires":["Cloudflare Workers account with build system enabled","Git repository or source code access for Worker scripts","API permissions for deployment and build management"],"input_types":["Worker script name or ID","Source code or Git commit reference","Deployment environment (preview or production)","Rollback target (deployment ID or version number)"],"output_types":["Build status (pending, compiling, succeeded, failed)","Build logs (compilation errors, warnings, asset sizes)","Deployment status (in-progress, completed, rolled back)","Deployment metadata (timestamp, region coverage, asset count)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_7","uri":"capability://memory.knowledge.autorag.and.vector.based.document.retrieval","name":"autorag and vector-based document retrieval","description":"Implements automatic Retrieval-Augmented Generation (RAG) capabilities through MCP tools that index documents into Cloudflare Vectorize, perform semantic search, and retrieve relevant context for LLM prompts. Uses vector embeddings to enable semantic similarity matching beyond keyword search, with support for document chunking, metadata filtering, and relevance scoring.","intents":["I want to build a knowledge base that my LLM can search semantically to answer questions","I need to retrieve relevant documentation or code snippets based on semantic similarity","I want to augment LLM responses with context from my own documents without fine-tuning"],"best_for":["Teams building LLM-powered customer support or documentation assistants","Developers implementing RAG systems without external vector databases","Organizations with large document repositories needing semantic search"],"limitations":["Vector embedding generation has latency (~100-500ms per document); bulk indexing requires batching","Vectorize has storage limits per account; very large document collections may require partitioning","Semantic search quality depends on embedding model; domain-specific documents may need fine-tuned embeddings"],"requires":["Cloudflare Vectorize enabled on account","Documents in supported formats (text, markdown, PDF with text extraction)","Embedding model selection (Cloudflare-hosted or external)"],"input_types":["Documents (text, markdown, or structured data)","Query string (natural language or semantic search terms)","Metadata filters (document type, date range, tags)","Search parameters (top-k results, similarity threshold)"],"output_types":["Ranked search results (document chunks with relevance scores)","Metadata for each result (source, date, tags)","Embedding vectors (for debugging or re-ranking)","Context snippets (formatted for LLM consumption)"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_8","uri":"capability://code.generation.editing.sandbox.container.execution.and.code.analysis","name":"sandbox container execution and code analysis","description":"Provides MCP tools for executing code in isolated sandbox containers and analyzing code structure through DEX (Dependency Explorer). Implements container lifecycle management (create, execute, cleanup) with resource limits (CPU, memory, timeout), and provides code analysis capabilities including dependency extraction, AST parsing, and security scanning.","intents":["I want to safely execute untrusted code snippets provided by users without risking the main application","I need to analyze code dependencies and structure to understand what a code snippet does","I want to run tests or validation scripts in an isolated environment"],"best_for":["LLM applications that need to execute user-provided code safely","Code analysis and security scanning tools","Development environments requiring isolated code execution"],"limitations":["Container startup time adds ~500ms-2s overhead per execution; not suitable for high-frequency operations","Resource limits (CPU, memory, timeout) may cause legitimate code to fail; limits must be tuned per use case","Network access from containers is restricted; code requiring external APIs must use allowlisted endpoints"],"requires":["Cloudflare sandbox container service enabled","Container image with required runtime (Node.js, Python, etc.)","Resource limit configuration (CPU cores, memory MB, timeout seconds)"],"input_types":["Code snippet (string or file path)","Execution environment (Node.js, Python, etc.)","Resource limits (CPU, memory, timeout)","Input data (stdin, environment variables)"],"output_types":["Execution result (stdout, stderr, exit code)","Resource usage (CPU time, memory peak, duration)","Code analysis (dependencies, AST, security issues)","Error details (timeout, out-of-memory, syntax errors)"],"categories":["code-generation-editing","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-cloudflare-mcp-server-cloudflare__cap_9","uri":"capability://data.processing.analysis.logpush.and.audit.log.streaming","name":"logpush and audit log streaming","description":"Exposes Cloudflare Logpush capabilities through MCP tools for configuring log delivery, querying audit logs, and analyzing security events. Implements integration with Cloudflare's audit log system to retrieve user actions, API calls, and security events with filtering by timestamp, action type, and resource, supporting both real-time streaming and historical log queries.","intents":["I want to understand who made changes to my Cloudflare configuration and when","I need to investigate security events and API calls for compliance auditing","I want to set up automated log delivery to my SIEM or data warehouse"],"best_for":["Security and compliance teams investigating configuration changes","Organizations requiring audit trails for regulatory compliance","Teams building security monitoring and alerting systems"],"limitations":["Audit logs have ~5-10 minute latency; real-time security events require separate alerting","Log retention is limited to 30 days; longer-term analysis requires external storage","Logpush delivery has eventual consistency; logs may arrive out-of-order or with duplicates"],"requires":["Cloudflare account with audit logging enabled","Logpush destination configured (S3, GCS, Splunk, etc.)","API permissions for reading audit logs"],"input_types":["Time range (start/end timestamps)","Filter criteria (action type, user, resource, result)","Log format preference (JSON, CSV)","Destination configuration (bucket, endpoint, credentials)"],"output_types":["Audit log entries (timestamp, user, action, resource, result)","Aggregated statistics (actions per user, changes per resource)","Security events (failed logins, permission changes, API errors)","Logpush job status (active, paused, error)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":36,"verified":false,"data_access_risk":"high","permissions":["Cloudflare account with Workers enabled","MCP client library compatible with HTTP streaming transport (e.g., Claude SDK, Anthropic SDK)","API token or OAuth 2.0 credentials for Cloudflare authentication","Cloudflare OAuth application registered in Cloudflare dashboard","Cloudflare API token with appropriate scopes (for token-based auth)","Durable Objects binding in Worker configuration for session state","Cloudflare documentation indexed in Vectorize","Embedding model for semantic search","Category metadata for filtering results","Cloudflare Browser Rendering service enabled"],"failure_modes":["Legacy SSE transport (/sse endpoint) is deprecated; HTTP streaming is primary transport","Each MCP server instance is stateless — requires external state management for multi-step workflows","Tool execution latency includes Cloudflare Worker cold-start overhead (~50-200ms on first invocation)","OAuth flow requires user interaction — not suitable for fully automated, headless scenarios","API token mode has no built-in rotation; tokens must be manually rotated and revoked","Durable Objects state storage has eventual consistency guarantees; immediate token revocation may have ~1-5s propagation delay","Documentation search quality depends on embedding model; technical jargon may not match user queries","Documentation is static; real-time API changes may not be reflected immediately","Code examples are limited to official Cloudflare documentation; community examples are not indexed","Browser rendering has high latency (~2-10 seconds per page); not suitable for real-time interactions","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3785746813777531,"quality":0.35,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.693Z","last_scraped_at":"2026-05-03T14:04:47.472Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":3907,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=cloudflare-mcp-server-cloudflare","compare_url":"https://unfragile.ai/compare?artifact=cloudflare-mcp-server-cloudflare"}},"signature":"WfAVn5bMXnxVUNQiUWcIVgCflQFY8qCk8BHLKtIoS9CCEjyTXk8/5Bw/jCyUJjwgmjmnGtE5oIElBpAyRzt4Cg==","signedAt":"2026-06-20T02:39:08.053Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/cloudflare-mcp-server-cloudflare","artifact":"https://unfragile.ai/cloudflare-mcp-server-cloudflare","verify":"https://unfragile.ai/api/v1/verify?slug=cloudflare-mcp-server-cloudflare","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}