{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github_mcp-iannuttall-mcp-boilerplate","slug":"mcp-iannuttall-mcp-boilerplate","name":"mcp-boilerplate","type":"mcp","url":"https://github.com/iannuttall/mcp-boilerplate","page_url":"https://unfragile.ai/mcp-iannuttall-mcp-boilerplate","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_0","uri":"capability://automation.workflow.cloudflare.workers.based.mcp.server.deployment.with.serverless.infrastructure","name":"cloudflare workers-based mcp server deployment with serverless infrastructure","description":"Deploys a Model Context Protocol server on Cloudflare Workers, providing a globally distributed, edge-compute endpoint for AI assistants. The system uses Cloudflare's KV storage for state management and integrates with external OAuth and Stripe services via HTTP APIs. Requests flow through a central /sse endpoint that handles Server-Sent Events for real-time tool execution and response streaming.","intents":["Deploy an MCP server without managing traditional infrastructure or containers","Build a globally distributed AI tool endpoint with minimal operational overhead","Create a production-ready MCP service that scales automatically with Cloudflare's edge network"],"best_for":["Solo developers and small teams building MCP tools","Developers wanting zero-ops deployment without managing servers","Teams building AI assistant integrations for Claude, Cursor, or other MCP-compatible clients"],"limitations":["Cloudflare Workers have a 30-second execution timeout per request, limiting long-running tool operations","KV storage has eventual consistency semantics, not suitable for strongly-consistent transactional operations","Cold starts on Cloudflare Workers are typically <50ms but can impact latency-sensitive operations","Limited to Cloudflare's runtime environment — no arbitrary system dependencies or native modules"],"requires":["Cloudflare account with Workers enabled","Node.js 18+ for local development","TypeScript knowledge for customization","Wrangler CLI for deployment"],"input_types":["HTTP POST requests with JSON payloads","Server-Sent Events (SSE) stream connections","OAuth tokens from Google or GitHub"],"output_types":["SSE-formatted streaming responses","JSON-structured tool results","Stripe checkout URLs for payment flows"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_1","uri":"capability://safety.moderation.oauth.based.user.authentication.with.google.and.github.identity.providers","name":"oauth-based user authentication with google and github identity providers","description":"Implements a dual-provider OAuth authentication system using the OAuthProvider class that verifies user identity through Google or GitHub. Authentication tokens are stored in Cloudflare KV storage (OAUTH_KV) and validated on each request. The system handles the OAuth redirect flow, token exchange, and session management without requiring users to create new credentials.","intents":["Authenticate users via their existing Google or GitHub accounts without building custom auth","Ensure only authorized users can access paid and free tools","Manage user sessions and tokens across multiple requests in a serverless environment"],"best_for":["Developers building tools for technical audiences familiar with GitHub/Google accounts","Teams wanting to avoid password management and credential storage complexity","MCP server builders needing quick user authentication without third-party auth services"],"limitations":["Only supports Google and GitHub OAuth — no email/password or other identity providers","KV storage eventual consistency means token validation may have slight delays in distributed scenarios","No built-in token refresh logic — tokens stored in KV may expire without automatic renewal","Session management relies entirely on KV storage, which has no built-in TTL enforcement"],"requires":["Google OAuth 2.0 credentials (Client ID and Secret)","GitHub OAuth App credentials (Client ID and Secret)","Cloudflare KV namespace bound to the Worker","Environment variables: GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, GITHUB_CLIENT_ID, GITHUB_CLIENT_SECRET"],"input_types":["OAuth authorization codes from Google/GitHub","User tokens in HTTP headers or request body","Redirect URIs for OAuth callback handling"],"output_types":["User identity objects with email and provider info","Authentication tokens stored in KV","OAuth redirect URLs for login flow initiation"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_10","uri":"capability://safety.moderation.tool.input.validation.using.json.schema.with.automatic.error.handling","name":"tool input validation using json schema with automatic error handling","description":"Validates tool inputs against JSON Schema definitions before execution, ensuring that only well-formed requests reach tool handlers. The system compares incoming tool parameters against the tool's declared inputSchema, rejects invalid inputs with detailed error messages, and prevents malformed requests from causing tool failures. Validation happens automatically as part of the tool execution pipeline.","intents":["Prevent malformed tool inputs from causing runtime errors or unexpected behavior","Provide clear error messages to AI assistants when they invoke tools incorrectly","Enforce type safety and required parameters without custom validation code in each tool"],"best_for":["Developers building robust MCP tools that handle untrusted input","Teams wanting to shift validation left and catch errors before tool execution","Builders needing to provide clear error feedback to AI assistants"],"limitations":["JSON Schema validation cannot express complex business logic constraints (e.g., 'email must be from company domain')","Validation errors are generic — developers must add custom error messages for domain-specific validation","Schema validation adds latency (typically <10ms) to each tool invocation","No built-in support for conditional validation (e.g., 'if type=A, then field X is required')","Schema changes require tool redeployment — no runtime schema updates"],"requires":["JSON Schema definitions for each tool's inputs","JSON Schema validator library (typically ajv or similar)","Tool metadata including inputSchema field"],"input_types":["JSON Schema objects defining tool input structure","Tool invocation parameters as JSON"],"output_types":["Validation success/failure status","Detailed error messages for invalid inputs","Validated input object passed to tool handler"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_11","uri":"capability://tool.use.integration.mcp.protocol.implementation.with.tool.discovery.and.dynamic.invocation","name":"mcp protocol implementation with tool discovery and dynamic invocation","description":"Implements the Model Context Protocol (MCP) specification, allowing AI assistants to discover available tools, inspect their schemas, and invoke them dynamically. The system exposes tool metadata (name, description, input schema) via MCP protocol messages, handles tool invocation requests, and returns results in MCP-compliant format. This enables seamless integration with MCP-compatible clients like Claude and Cursor.","intents":["Enable AI assistants to discover and invoke custom tools without hardcoded integrations","Provide standardized tool metadata that AI assistants can use to understand tool capabilities","Support dynamic tool invocation where AI assistants choose which tools to call based on context"],"best_for":["Developers building AI assistant integrations for Claude, Cursor, or other MCP clients","Teams wanting to expose tools to multiple AI assistants through a single interface","Builders creating extensible tool ecosystems that AI assistants can discover dynamically"],"limitations":["MCP protocol is relatively new — not all AI assistants support it yet","Tool discovery is static at deployment time — dynamic tool registration requires redeployment","MCP protocol has limited support for streaming results — large outputs may be chunked","No built-in versioning for tool schemas — breaking changes require careful migration","AI assistants may not understand complex tool descriptions, leading to misuse"],"requires":["MCP-compatible AI assistant client (Claude, Cursor, etc.)","Tool metadata: name, description, input schema","MCP protocol implementation (provided by the boilerplate)"],"input_types":["MCP protocol messages (tool discovery requests, invocation requests)","Tool metadata objects","Tool handler functions"],"output_types":["MCP tool definitions (name, description, schema)","Tool invocation results in MCP-compliant format","Error messages and execution status"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_12","uri":"capability://automation.workflow.request.flow.orchestration.with.authentication.payment.and.tool.execution","name":"request flow orchestration with authentication, payment, and tool execution","description":"Orchestrates the complete request lifecycle from initial connection through authentication, payment validation, tool execution, and response streaming. The system validates OAuth tokens, checks payment status (if applicable), validates tool inputs, executes the tool handler, and streams results via SSE. Each step is enforced in sequence — requests fail fast if authentication or payment checks fail, preventing unnecessary tool execution.","intents":["Ensure requests are authenticated and authorized before tool execution","Validate payment status and prevent unpaid users from accessing premium tools","Execute tools safely with proper error handling and response streaming"],"best_for":["Developers building secure MCP servers with authentication and payment requirements","Teams needing to enforce access control policies across multiple tools","Builders wanting to prevent unauthorized or unpaid access without custom middleware"],"limitations":["Request orchestration adds latency (authentication ~50ms, payment check ~200-500ms, validation ~10ms)","Failures at any step terminate the request — no partial execution or fallback mechanisms","Error messages may leak information about authentication or payment status","No built-in rate limiting or request throttling — high-volume requests may overwhelm the system","Concurrent requests are not queued — simultaneous requests may cause resource contention"],"requires":["Valid OAuth token in request headers","Tool identifier and input parameters in request body","Stripe API key for payment validation (if tool is paid)","Tool handler function with proper error handling"],"input_types":["HTTP POST requests with authentication headers","Tool invocation details (tool ID, input parameters)","OAuth tokens and user identifiers"],"output_types":["SSE-formatted response stream","Tool execution results","Error messages and status codes"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_13","uri":"capability://safety.moderation.error.handling.and.user.feedback.with.detailed.validation.and.execution.error.messages","name":"error handling and user feedback with detailed validation and execution error messages","description":"Provides structured error handling throughout the request lifecycle, returning detailed error messages for authentication failures, payment validation failures, input validation errors, and tool execution errors. Errors are formatted as JSON responses or SSE messages, allowing AI assistants to understand what went wrong and potentially retry or adjust their requests. Error messages include context (which step failed, why) without leaking sensitive information.","intents":["Provide clear error feedback to AI assistants when requests fail","Help developers debug tool failures and integration issues","Prevent information leaks by sanitizing error messages"],"best_for":["Developers building user-friendly MCP servers with clear error feedback","Teams needing to debug tool failures and integration issues","Builders wanting to improve AI assistant behavior through better error messages"],"limitations":["Error messages may be too generic for complex debugging scenarios","No built-in error logging or monitoring — developers must implement custom logging","Error context is limited to the current request — no cross-request error tracking","Sensitive error details (stack traces, API keys) must be manually filtered","No built-in error recovery or retry logic — clients must handle retries"],"requires":["Error handling code in tool handlers","Structured error response format (JSON or SSE)","Error message templates for common failure scenarios"],"input_types":["Exceptions and errors from tool handlers","Validation failures from input schema checks","Authentication and payment validation failures"],"output_types":["JSON error responses with error code and message","SSE error messages with context","HTTP status codes (401, 403, 400, 500, etc.)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_2","uri":"capability://automation.workflow.stripe.integrated.payment.processing.with.three.monetization.models","name":"stripe-integrated payment processing with three monetization models","description":"Integrates Stripe payment processing through the PaidMcpAgent class, supporting three distinct payment models: subscription-based (recurring charges), metered usage (pay-per-use), and one-time payments. Before a user accesses a paid tool, the system checks their payment status via Stripe API; unpaid users receive a checkout URL. Payment history and subscription status are tracked and validated on each tool invocation.","intents":["Monetize AI tools through flexible payment models (subscriptions, usage-based, or one-time)","Prevent unauthorized access to paid tools by validating payment status before execution","Track user payment history and manage subscription lifecycle without building custom billing infrastructure"],"best_for":["Developers building commercial MCP tools with recurring revenue models","Teams wanting to offer tiered access (free + premium tools) without custom billing systems","Builders needing usage-based pricing for compute-intensive or API-heavy tools"],"limitations":["Stripe API calls add 200-500ms latency per tool invocation for payment validation","No built-in retry logic for failed Stripe API calls — payment checks may fail if Stripe is unavailable","Metered usage tracking requires manual event submission to Stripe; no automatic usage aggregation","Subscription validation is point-in-time; users with lapsed subscriptions may have brief access windows before revocation","Checkout URLs are single-use and expire after 24 hours, requiring re-generation for repeat attempts"],"requires":["Stripe account with API keys (publishable and secret)","Environment variables: STRIPE_SECRET_KEY, STRIPE_PUBLISHABLE_KEY","Stripe product and price IDs configured for each paid tool","Webhook endpoint for Stripe events (optional but recommended for subscription updates)"],"input_types":["User ID and tool identifier for payment status checks","Usage metrics for metered billing (units consumed, timestamps)","Stripe webhook payloads for subscription state changes"],"output_types":["Boolean payment status (paid/unpaid)","Stripe checkout URLs for payment initiation","Payment history records with timestamps and amounts","Subscription status objects with renewal dates"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_3","uri":"capability://tool.use.integration.tool.registration.and.execution.framework.with.free.and.paid.tool.support","name":"tool registration and execution framework with free and paid tool support","description":"Provides a declarative tool registration system where developers define tools (free or paid) with metadata including name, description, input schema, and payment model. The BoilerplateMCP class (extending PaidMcpAgent) manages tool registration, validates input against schemas, executes tool handlers, and enforces payment requirements. Tools are exposed via the MCP protocol, allowing AI assistants to discover and invoke them dynamically.","intents":["Define custom tools that AI assistants can discover and invoke without manual integration","Create both free and paid tools within a single framework without duplicating infrastructure","Validate tool inputs against JSON schemas before execution to prevent malformed requests"],"best_for":["Developers building tool ecosystems for AI assistants (Claude, Cursor, etc.)","Teams wanting to expose internal APIs as discoverable MCP tools","Builders creating mixed free/premium tool offerings with unified management"],"limitations":["Tool execution is synchronous — long-running operations (>30 seconds) will timeout on Cloudflare Workers","Input validation uses JSON Schema, which may not capture complex business logic constraints","No built-in tool versioning — updating tool schemas requires redeployment","Tool discovery is static at deployment time; dynamic tool registration requires code changes","Error handling is basic — tool failures return generic error messages without detailed debugging context"],"requires":["TypeScript for tool implementation","JSON Schema definitions for tool input validation","Tool handler functions with signature: (input: Record<string, unknown>) => Promise<unknown>","Tool metadata: name, description, inputSchema, and optional paymentModel"],"input_types":["Tool metadata objects (name, description, schema)","User input matching tool's JSON Schema","Tool handler functions (async callbacks)"],"output_types":["Tool execution results (any JSON-serializable type)","MCP tool definitions for client discovery","Error messages and validation failures"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_4","uri":"capability://automation.workflow.subscription.based.recurring.payment.model.with.automatic.access.control","name":"subscription-based recurring payment model with automatic access control","description":"Implements a subscription payment model where users pay recurring fees (monthly, yearly, etc.) for continuous access to tools. The system checks Stripe subscription status on each tool invocation; active subscriptions grant access, while expired or canceled subscriptions deny access and provide a renewal checkout URL. Subscription state is validated against Stripe's authoritative records, not cached locally.","intents":["Charge users recurring fees for ongoing access to premium tools","Automatically revoke tool access when subscriptions expire or are canceled","Provide seamless renewal flows when subscriptions lapse"],"best_for":["Developers building SaaS-style MCP tools with predictable recurring revenue","Teams offering tiered access (free tier + premium subscription)","Builders wanting simple, predictable billing without usage tracking complexity"],"limitations":["Stripe API calls for subscription validation add 200-500ms latency per tool invocation","No local caching of subscription status — every tool call requires a Stripe API round-trip","Subscription state changes (cancellation, renewal) may take seconds to reflect in access control","No built-in grace periods — access is revoked immediately upon subscription expiration","Requires manual Stripe webhook handling to update subscription state in real-time"],"requires":["Stripe account with subscription products and prices configured","Environment variables: STRIPE_SECRET_KEY","Stripe product IDs and price IDs for subscription tiers","User-to-Stripe-customer mapping (stored in KV or external database)"],"input_types":["User ID for subscription lookup","Tool identifier to determine which subscription is required","Stripe customer ID (derived from user ID)"],"output_types":["Boolean subscription status (active/inactive)","Stripe checkout URL for subscription purchase/renewal","Subscription metadata (renewal date, price, interval)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_5","uri":"capability://automation.workflow.metered.usage.based.billing.with.pay.per.use.pricing.model","name":"metered usage-based billing with pay-per-use pricing model","description":"Implements a metered billing model where users are charged based on actual tool usage (e.g., per API call, per unit processed). Developers submit usage events to Stripe, which aggregates them and charges users according to configured meter rates. Access control checks whether the user has an active metered billing subscription; usage is tracked separately and billed at the end of the billing cycle.","intents":["Charge users based on actual tool consumption rather than fixed subscriptions","Track and bill for variable-cost operations (API calls, data processing, etc.)","Provide transparent usage-based pricing without overcharging for unused capacity"],"best_for":["Developers building compute-intensive or API-heavy tools with variable costs","Teams wanting to align pricing with actual resource consumption","Builders offering tools where usage varies dramatically between users"],"limitations":["Requires manual event submission to Stripe for each usage occurrence — no automatic aggregation","Stripe metered billing has a 1-hour aggregation window, so charges may not reflect real-time usage","No built-in usage forecasting or alerts — users may be surprised by high bills","Metered events submitted to Stripe are immutable; corrections require manual Stripe API calls","Requires careful event design to avoid double-counting or missing usage"],"requires":["Stripe account with metered billing products configured","Environment variables: STRIPE_SECRET_KEY","Stripe meter event submission API integration","Usage event schema definition (what constitutes one unit of usage)"],"input_types":["Usage metrics (quantity, unit type, timestamp)","User ID for billing attribution","Tool identifier to determine which meter to increment"],"output_types":["Confirmation of usage event submission to Stripe","Current usage totals for the billing period","Estimated charges based on current usage"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_6","uri":"capability://automation.workflow.one.time.payment.model.for.single.use.or.perpetual.tool.access","name":"one-time payment model for single-use or perpetual tool access","description":"Implements a one-time payment model where users pay once for permanent or perpetual access to a tool. After payment is confirmed, the system records the purchase in Stripe and grants indefinite access without requiring renewal. Access control checks whether a user has completed the one-time payment; if not, they receive a checkout URL.","intents":["Sell tools with one-time payments for permanent access","Offer perpetual licenses without subscription management overhead","Provide simple, transparent pricing for tools with no recurring costs"],"best_for":["Developers selling standalone tools or utilities with one-time fees","Teams offering perpetual licenses without subscription complexity","Builders wanting simple, low-friction monetization for niche tools"],"limitations":["No recurring revenue — requires continuous new customer acquisition","No built-in upgrade path — users who paid for v1 don't automatically get v2","Payment status is permanent — no way to revoke access for non-compliance","Stripe checkout URLs expire after 24 hours, requiring regeneration for repeat purchase attempts","No usage limits or rate limiting — paid users have unlimited access"],"requires":["Stripe account with one-time payment products configured","Environment variables: STRIPE_SECRET_KEY","Stripe product IDs and price IDs for one-time purchases","User-to-payment mapping (stored in KV or external database)"],"input_types":["User ID for payment status lookup","Tool identifier to determine which product was purchased","Stripe customer ID (derived from user ID)"],"output_types":["Boolean payment status (purchased/not purchased)","Stripe checkout URL for initial purchase","Payment confirmation details (date, amount)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_7","uri":"capability://automation.workflow.server.sent.events.sse.streaming.response.protocol.for.real.time.tool.output","name":"server-sent events (sse) streaming response protocol for real-time tool output","description":"Implements the /sse endpoint using Server-Sent Events to stream tool execution results back to AI assistants in real-time. The system establishes a persistent connection, executes tools, and sends results as SSE-formatted messages. This allows AI assistants to receive tool outputs incrementally rather than waiting for complete execution, enabling responsive interactions.","intents":["Stream tool results to AI assistants in real-time without waiting for complete execution","Provide responsive feedback for long-running tool operations","Enable AI assistants to process tool outputs incrementally and adjust behavior mid-stream"],"best_for":["Developers building interactive AI assistant integrations","Teams needing real-time feedback from tool execution","Builders creating responsive MCP servers for latency-sensitive applications"],"limitations":["SSE connections are unidirectional (server-to-client only) — clients cannot send mid-stream commands","Cloudflare Workers have a 30-second timeout, limiting SSE stream duration","Network interruptions terminate the SSE connection without automatic reconnection","Large tool outputs may be chunked across multiple SSE messages, requiring client-side reassembly","Browser-based clients may have CORS restrictions on SSE connections"],"requires":["HTTP client supporting SSE (most modern browsers and HTTP libraries)","Cloudflare Workers runtime with SSE support","Tool handlers that can produce streaming output or multiple result chunks"],"input_types":["HTTP POST requests with tool invocation details","Tool input parameters as JSON","User authentication tokens in headers"],"output_types":["SSE-formatted message stream (text/event-stream MIME type)","JSON-encoded tool results in SSE data fields","Error messages and execution status updates"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_8","uri":"capability://memory.knowledge.cloudflare.kv.based.session.and.token.storage.with.eventual.consistency.semantics","name":"cloudflare kv-based session and token storage with eventual consistency semantics","description":"Uses Cloudflare KV (key-value store) as the primary data store for OAuth tokens, user sessions, and payment state. The system stores authentication tokens with optional TTL, retrieves them on subsequent requests, and manages user session lifecycle. KV provides distributed, edge-local storage without requiring external databases, but with eventual consistency guarantees rather than strong consistency.","intents":["Store user sessions and OAuth tokens without external database dependencies","Maintain user state across multiple Cloudflare Worker instances globally","Implement fast, edge-local session lookups without round-trips to central databases"],"best_for":["Developers building stateless MCP servers without database infrastructure","Teams wanting to minimize external service dependencies","Builders prioritizing deployment simplicity over strong consistency guarantees"],"limitations":["KV has eventual consistency — writes may not be immediately visible across all edge locations","No built-in TTL enforcement — expired tokens may remain in KV until manually deleted","KV has a 25MB value size limit per key, limiting large session objects","No transactions or atomic operations — concurrent updates may cause data loss","KV pricing scales with read/write volume; high-traffic servers may incur significant costs"],"requires":["Cloudflare account with KV enabled","KV namespace binding in wrangler.toml (e.g., OAUTH_KV)","Environment variable: OAUTH_KV (namespace binding name)","Understanding of eventual consistency semantics"],"input_types":["Key-value pairs (string keys, JSON values)","TTL values in seconds for automatic expiration","User IDs and token strings for session storage"],"output_types":["Retrieved session objects or tokens","Confirmation of write operations","Null/undefined for missing keys"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-iannuttall-mcp-boilerplate__cap_9","uri":"capability://automation.workflow.environment.based.configuration.management.for.multi.environment.deployments","name":"environment-based configuration management for multi-environment deployments","description":"Supports environment-specific configuration through environment variables and wrangler.toml settings, allowing developers to deploy the same codebase to development, staging, and production with different configurations. Variables include OAuth credentials, Stripe keys, KV namespace bindings, and deployment targets. The system reads configuration at Worker initialization time and uses it throughout the request lifecycle.","intents":["Deploy the same MCP server code to multiple environments with different credentials","Manage sensitive credentials (API keys, secrets) without hardcoding them","Configure environment-specific behavior (logging, rate limits, feature flags)"],"best_for":["Teams managing development, staging, and production deployments","Developers wanting to avoid credential leaks through version control","Builders needing environment-specific feature toggles or behavior"],"limitations":["Environment variables are set at deployment time — runtime changes require redeployment","No built-in secret rotation — credentials must be manually updated in Cloudflare dashboard","Wrangler.toml is version-controlled, so environment-specific secrets cannot be stored there","No built-in validation of required environment variables — missing configs cause runtime errors","Cloudflare dashboard UI for managing secrets is limited compared to dedicated secret management tools"],"requires":["Wrangler CLI for managing environment variables","Cloudflare account with access to environment variable settings","Environment variables: GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, GITHUB_CLIENT_ID, GITHUB_CLIENT_SECRET, STRIPE_SECRET_KEY, STRIPE_PUBLISHABLE_KEY","KV namespace bindings configured in wrangler.toml"],"input_types":["Environment variable names and values","Wrangler.toml configuration sections","Cloudflare dashboard environment variable UI"],"output_types":["Loaded configuration objects at Worker initialization","Runtime access to environment variables via process.env or Cloudflare bindings"],"categories":["automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Cloudflare account with Workers enabled","Node.js 18+ for local development","TypeScript knowledge for customization","Wrangler CLI for deployment","Google OAuth 2.0 credentials (Client ID and Secret)","GitHub OAuth App credentials (Client ID and Secret)","Cloudflare KV namespace bound to the Worker","Environment variables: GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET, GITHUB_CLIENT_ID, GITHUB_CLIENT_SECRET","JSON Schema definitions for each tool's inputs","JSON Schema validator library (typically ajv or similar)"],"failure_modes":["Cloudflare Workers have a 30-second execution timeout per request, limiting long-running tool operations","KV storage has eventual consistency semantics, not suitable for strongly-consistent transactional operations","Cold starts on Cloudflare Workers are typically <50ms but can impact latency-sensitive operations","Limited to Cloudflare's runtime environment — no arbitrary system dependencies or native modules","Only supports Google and GitHub OAuth — no email/password or other identity providers","KV storage eventual consistency means token validation may have slight delays in distributed scenarios","No built-in token refresh logic — tokens stored in KV may expire without automatic renewal","Session management relies entirely on KV storage, which has no built-in TTL enforcement","JSON Schema validation cannot express complex business logic constraints (e.g., 'email must be from company domain')","Validation errors are generic — developers must add custom error messages for domain-specific validation","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.44646883626512024,"quality":0.35,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.6,"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":"2026-05-24T12:16:22.065Z","last_scraped_at":"2026-05-03T14:23:44.761Z","last_commit":"2026-02-04T13:38:36Z"},"community":{"stars":1021,"forks":196,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-iannuttall-mcp-boilerplate","compare_url":"https://unfragile.ai/compare?artifact=mcp-iannuttall-mcp-boilerplate"}},"signature":"qm9cO9DL/Y34e+8hDDB4leLAF01szsANf5kf2jfYkuKLXSicPciPxvB5KvG2onx5PamzPecBJCn7eNj8W9DDAw==","signedAt":"2026-06-20T06:06:12.790Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-iannuttall-mcp-boilerplate","artifact":"https://unfragile.ai/mcp-iannuttall-mcp-boilerplate","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-iannuttall-mcp-boilerplate","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"}}