| Ecosystem | 1 | 1 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 13 decomposed | 12 decomposed |
| Times Matched | 0 | 0 |
Automatically discovers and registers MCP tools, prompts, and resources by scanning the file system directory structure, eliminating manual route registration. The framework uses a convention-over-configuration approach where files in designated directories (e.g., src/tools/, src/prompts/, src/resources/) are automatically compiled into MCP-compatible handlers without explicit routing declarations. This pattern reduces boilerplate and enables hot-reloading during development by watching file changes and recompiling affected routes.
Unique: Uses file system directory structure as the source of truth for MCP endpoint discovery, eliminating manual route registration entirely. Unlike traditional MCP frameworks requiring explicit handler registration, xmcp scans designated directories and auto-compiles discovered files into MCP-compatible handlers with hot-reload support.
vs alternatives: Reduces boilerplate by ~70% compared to manual MCP server implementations that require explicit tool/prompt registration, and matches the developer experience of Next.js file-based routing which TypeScript developers already understand.
Monitors source files for changes and automatically recompiles and reloads MCP handlers without requiring server restart, enabling rapid iteration during development. The framework watches designated directories (tools, prompts, resources) and triggers incremental compilation via webpack, then hot-swaps handler modules in the running process. This is implemented through a development-mode transport layer that intercepts file system events and coordinates recompilation with the MCP server lifecycle.
Unique: Implements hot-reloading at the MCP handler level by watching file system changes and performing incremental webpack compilation with module hot-swapping, rather than requiring full server restarts. This is coordinated with the MCP transport layer to ensure handlers are reloaded before new client requests arrive.
vs alternatives: Faster development feedback than nodemon-based approaches (which restart the entire process), and more granular than generic file watchers because it understands MCP handler semantics and only recompiles affected routes.
Maintains a collection of 20+ example projects (in examples/ directory) demonstrating xmcp patterns, middleware implementations, transport configurations, and integrations with external services. Each example is a complete, runnable project that showcases specific xmcp features (e.g., authentication, custom middleware, serverless deployment). Examples serve as both learning resources and starting points for developers building similar applications.
Unique: Provides a curated collection of 20+ complete, runnable example projects covering common xmcp patterns (authentication, middleware, transports, integrations). Each example is a self-contained project that can be cloned and run independently, serving as both learning resources and starting points for similar applications.
vs alternatives: More comprehensive than code snippets in documentation because examples are complete, runnable projects that demonstrate real-world patterns and edge cases.
Provides a plugin architecture (packages/plugins/*) that allows third-party developers to extend xmcp with additional functionality without modifying the core framework. Plugins can add new middleware, authentication providers, transport adapters, or tool integrations. The plugin system uses a standard interface that plugins implement, and the framework automatically discovers and loads plugins from the node_modules directory or explicit configuration.
Unique: Implements a plugin system that allows third-party developers to extend xmcp with custom middleware, authentication providers, and transport adapters. Official plugins (better-auth, polar) demonstrate the pattern and provide commonly-needed functionality without bloating the core framework.
vs alternatives: More modular than monolithic frameworks where all features are built-in, and enables community contributions without requiring core framework changes.
Organizes the xmcp project as a pnpm monorepo with separate packages for the core framework (packages/xmcp), CLI tools (packages/create-xmcp-app, packages/init-xmcp), plugins (packages/plugins/*), documentation website (apps/website), and examples (examples/*). This structure enables independent versioning and publishing of each package while maintaining shared dependencies and coordinated development. pnpm workspaces handle dependency resolution and linking, reducing duplication and ensuring consistency across packages.
Unique: Uses pnpm workspaces to organize the xmcp project as a monorepo with separate packages for the core framework, CLI tools, plugins, documentation, and examples. This enables independent versioning and publishing while maintaining shared dependencies and coordinated development.
vs alternatives: More efficient than separate repositories because pnpm deduplicates dependencies and enables atomic commits across packages. More maintainable than a single package because each component can be versioned and published independently.
Abstracts MCP server implementation from transport protocol, allowing the same tool/prompt/resource definitions to be deployed via HTTP, STDIO, or serverless platforms (AWS Lambda, Vercel Functions) without code changes. The framework defines a transport interface that handles protocol-specific serialization, request routing, and response formatting. Each transport (http.ts, stdio.ts, adapters/) implements this interface, and the core framework compiles tools into a transport-agnostic handler registry that each transport consumes.
Unique: Defines a transport abstraction layer that decouples MCP handler logic from protocol implementation, allowing a single tool/prompt/resource codebase to be compiled into HTTP, STDIO, or serverless handlers. This is achieved through a transport interface that each protocol implementation extends, with the core framework compiling to a transport-agnostic handler registry.
vs alternatives: Eliminates code duplication across transports compared to building separate HTTP and STDIO servers, and provides first-class serverless support that generic MCP frameworks require custom adapters to achieve.
Provides a middleware pipeline architecture that intercepts MCP requests before they reach tool handlers, enabling authentication, logging, rate-limiting, and request transformation. Middleware is implemented as composable functions that receive the request context (including authentication state) and can modify or reject requests before handler execution. The framework includes built-in middleware for API key validation (api-key.ts) and JWT verification (jwt.ts), and allows custom middleware to be registered globally or per-tool via configuration.
Unique: Implements a composable middleware pipeline that intercepts MCP requests before handler execution, with built-in support for API key and JWT authentication. Unlike monolithic authentication approaches, middleware can be selectively applied per-tool or globally, and custom middleware can be injected to implement domain-specific logic (rate-limiting, logging, etc.).
vs alternatives: More flexible than hard-coded authentication in tool handlers, and provides cleaner separation of concerns than frameworks requiring authentication logic in every tool definition.
Provides TypeScript interfaces and type definitions that enable compile-time validation of MCP tool signatures, parameter schemas, and response types. The framework exports core types (Tool, Prompt, Resource, etc.) that developers use to define MCP artifacts with full IDE autocomplete and type checking. Tool parameters are defined as TypeScript types, which are automatically converted to JSON Schema for MCP protocol compliance, ensuring type safety from development through runtime.
Unique: Leverages TypeScript's type system to define MCP artifacts with compile-time validation, automatically converting TypeScript types to JSON Schema for MCP protocol compliance. This eliminates the manual schema-writing burden and ensures type consistency between tool definitions and their MCP representations.
vs alternatives: Provides better developer experience than frameworks requiring manual JSON Schema definitions, and catches type mismatches at compile-time rather than runtime.
+5 more capabilities
Crawls 11+ heterogeneous platforms (Zhihu, Weibo, Bilibili, Twitter, Reddit, HackerNews, etc.) and RSS feeds using platform-specific scrapers, normalizes disparate data schemas into a unified NewsItem model, and deduplicates content across sources using fuzzy title matching and URL canonicalization. The system maintains platform-specific metadata (rank, heat value, engagement metrics) while presenting a single normalized feed, enabling cross-platform trend detection that would be invisible within individual platform silos.
Unique: Implements platform-specific crawler modules with unified NewsItem schema and fuzzy deduplication across 11+ heterogeneous sources (Chinese + international), rather than relying on single-platform APIs or generic RSS parsing. Maintains platform-specific metadata (rank × 0.6 + frequency × 0.3 + platform hot value × 0.1) for weighted hotspot scoring.
vs alternatives: Covers more platforms (especially Chinese social media) with deeper metadata extraction than generic RSS aggregators, and provides unified deduplication across sources unlike single-platform monitoring tools.
Implements a multi-stage filtering pipeline that matches news items against user-defined keywords using regex patterns, required word lists, and excluded word lists. The system applies frequency-based scoring (keyword occurrence count) combined with platform hotspot weights to rank filtered results. Configuration is stored in frequency_words.txt with support for regex patterns, AND/OR/NOT boolean operators, and per-keyword weighting. Filtering occurs at collection time (reducing storage) and again at report generation time (enabling dynamic reconfiguration without re-crawling).
Unique: Combines regex pattern matching with frequency-based scoring and platform hotspot weighting (rank × 0.6 + frequency × 0.3 + platform hot value × 0.1) in a two-stage pipeline (collection-time and report-time filtering). Supports dynamic reconfiguration without re-crawling by applying filters at report generation.
TrendRadar scores higher at 58/100 vs xmcp at 37/100.
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vs alternatives: More flexible than simple keyword matching (supports regex and boolean logic) and more efficient than semantic filtering (no LLM overhead), making it suitable for real-time filtering at scale.
Detects newly emerged topics by comparing current crawl results against historical data stored in the system. Topics are marked as 🆕 (new) if they appear for the first time in the current crawl or if their hotspot rank increased significantly compared to previous crawls. The system tracks topic emergence velocity (how quickly a topic rises in rankings) and flags topics with unusual acceleration. New topic detection is performed at report generation time, enabling dynamic detection without re-crawling. The system maintains a historical hotspot index for comparison.
Unique: Detects new topics by comparing current hotspot rankings against historical data, marking topics with significant rank increases as 🆕. Tracks emergence velocity to distinguish breaking news from sustained trends.
vs alternatives: More efficient than semantic similarity detection (no LLM overhead) and more accurate than simple first-appearance detection (accounts for re-emerging topics), but requires historical baseline data.
Provides a web-based UI for editing TrendRadar configuration files (config.yaml, frequency_words.txt, timeline.yaml) with real-time validation and preview. The editor supports: (1) syntax highlighting for YAML and regex, (2) validation of keyword patterns (regex compilation check), (3) preview of filtered results based on current keyword configuration, (4) drag-and-drop channel configuration, (5) schedule preview (shows next 10 execution times). Changes are validated before saving, preventing configuration errors. The editor is optional; users can edit config files directly.
Unique: Provides web-based configuration editor with real-time validation, regex preview, and schedule visualization. Enables non-technical users to configure TrendRadar without editing YAML files.
vs alternatives: More user-friendly than manual YAML editing and provides validation feedback, but adds operational complexity compared to file-based configuration.
Integrates LiteLLM to provide vendor-agnostic AI analysis and summarization of filtered news items. Users configure their preferred LLM provider (OpenAI, Anthropic, Ollama, local models, etc.) once in config.yaml, and the system automatically routes analysis requests to that provider. The AI analysis capability includes: (1) automated summarization of long articles into key points, (2) sentiment analysis (positive/negative/neutral), (3) trend prediction based on historical patterns, and (4) custom analysis prompts. Analysis results are cached to avoid redundant API calls and can be pushed directly to notification channels.
Unique: Uses LiteLLM abstraction layer to support any LLM provider (OpenAI, Anthropic, Ollama, local models) with single configuration, enabling provider switching without code changes. Caches analysis results to reduce redundant API calls and costs.
vs alternatives: More flexible than hardcoded OpenAI integration (supports any LiteLLM provider) and cheaper than dedicated sentiment analysis APIs (can use local models), but slower than rule-based sentiment analysis.
Leverages LiteLLM to translate news content from source languages (primarily Chinese) to target languages (English, etc.) on-demand. The system detects source language automatically (via langdetect or similar), caches translations to avoid re-translating identical content, and batches translation requests to reduce API calls. Translations are stored alongside original content, enabling bilingual reports and multi-language notification delivery. Translation can be triggered at collection time (all news) or report time (only filtered news).
Unique: Implements provider-agnostic translation via LiteLLM with automatic language detection, content-based caching, and batch request optimization. Stores translations alongside originals for bilingual report generation.
vs alternatives: More flexible than dedicated translation APIs (supports any LiteLLM provider) and cheaper than commercial translation services when using local models, but slower than specialized translation APIs.
Implements a notification abstraction layer supporting 9+ delivery channels (WeChat, WeWork, Feishu, Telegram, Email, ntfy, Bark, Slack, etc.). Each channel has a provider-specific formatter that converts normalized news items into channel-appropriate messages (e.g., WeChat card format, Telegram markdown, email HTML). The system batches notifications atomically—all news items for a report are sent as a single batch to each channel, ensuring consistency and reducing API calls. Message formatting respects channel constraints (character limits, attachment limits, etc.) and supports templating for customization.
Unique: Implements atomic message batching across 9+ heterogeneous channels with provider-specific formatters and constraint-aware truncation. Single configuration enables simultaneous delivery to WeChat, WeWork, Feishu, Telegram, Email, ntfy, Bark, Slack, etc. without code changes.
vs alternatives: Supports more channels (especially Chinese platforms like WeWork, Feishu) than generic notification services, and batching reduces API calls and spam compared to per-item notifications.
Exposes TrendRadar's data and analysis capabilities as an MCP server, enabling AI agents and LLM applications to query trends, perform analysis, and generate insights through natural language. The MCP server implements tools for: (1) querying filtered news by keyword/date/platform, (2) retrieving trend statistics and hotspot rankings, (3) running custom analysis on news subsets, (4) generating reports in various formats. Clients (Claude, other LLM agents) can invoke these tools via MCP protocol, enabling conversational exploration of trends without direct database access. The server maintains state across multiple requests, allowing multi-turn conversations about trends.
Unique: Implements full MCP server exposing trend data and analysis tools to LLM agents, enabling conversational queries and multi-turn analysis workflows. Maintains state across requests and supports complex tool invocations (filtering, analysis, report generation).
vs alternatives: Enables conversational access to trends (vs. API-only access) and integrates with LLM agent workflows (vs. standalone tools), but adds operational complexity compared to simple REST APIs.
+4 more capabilities