{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-websearch-mcp","slug":"websearch-mcp","name":"WebSearch-MCP","type":"mcp","url":"https://github.com/mnhlt/WebSearch-MCP","page_url":"https://unfragile.ai/websearch-mcp","categories":["mcp-servers"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-websearch-mcp__cap_0","uri":"capability://tool.use.integration.mcp.compliant.web.search.tool.exposure","name":"mcp-compliant web search tool exposure","description":"Implements the Model Context Protocol (MCP) server specification to expose a standardized web_search tool that AI assistants can invoke via stdio transport. The server translates tool calls from MCP-compatible clients (Claude Desktop, Cursor, Cline) into internal search requests and marshals results back through the MCP protocol layer, enabling seamless integration without custom client-side code.","intents":["Enable Claude or other MCP-compatible AI assistants to perform real-time web searches within their native interfaces","Integrate web search capabilities into existing MCP client applications without modifying client code","Provide a standardized interface for multiple AI clients to access the same web search backend"],"best_for":["Teams building AI applications with Claude Desktop, Cursor IDE, or Cline that need real-time web access","Developers integrating web search into MCP-compatible workflows without custom protocol implementation","Organizations standardizing on MCP for tool orchestration across multiple AI clients"],"limitations":["Requires MCP-compatible client — cannot be used with non-MCP AI assistants or APIs","Stdio transport adds latency for each search request — not suitable for high-frequency polling scenarios","No built-in caching or result deduplication across multiple identical search requests"],"requires":["Node.js 16+ (npm package distribution)","MCP-compatible client with stdio transport support","WebSearch Crawler API running and accessible (Docker container or remote instance)"],"input_types":["tool invocation with query string and optional filter parameters (domain, language, region, exclude terms)"],"output_types":["structured JSON with search results array containing title, snippet, URL, and metadata per result"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_1","uri":"capability://search.retrieval.real.time.web.search.with.anti.bot.bypass","name":"real-time web search with anti-bot bypass","description":"Delegates search execution to a containerized WebSearch Crawler API that integrates with FlareSolverr to bypass Cloudflare and other anti-bot protections, enabling searches on protected domains. The crawler handles the low-level HTTP mechanics, JavaScript rendering, and bot detection evasion, returning structured JSON results that the MCP server formats for client consumption.","intents":["Search websites protected by Cloudflare or similar anti-bot systems without being blocked","Retrieve current web information that overcomes the AI model's knowledge cutoff limitations","Access search results from domains that block standard HTTP requests or require JavaScript rendering"],"best_for":["Developers needing to search protected websites from AI agents without manual intervention","Teams running self-hosted search infrastructure to avoid rate limits and IP bans from public search APIs","Organizations requiring on-premises web search without relying on third-party search engine APIs"],"limitations":["FlareSolverr integration adds 2-5 second latency per search due to browser automation overhead","Crawler API must be running as separate Docker container — adds operational complexity vs. serverless alternatives","No built-in rate limiting or request queuing — high-volume searches may overwhelm the crawler instance","Search results depend on crawler's ability to parse HTML — JavaScript-heavy sites may return incomplete data"],"requires":["Docker runtime for WebSearch Crawler API container","FlareSolverr container running and accessible to crawler (for Cloudflare bypass)","Network connectivity from MCP server to Crawler API endpoint","Sufficient memory/CPU for concurrent search requests (crawler is CPU-bound during rendering)"],"input_types":["search query string","optional filter parameters: domain whitelist, language code, region, excluded terms"],"output_types":["JSON array of search results with title, snippet, URL, domain, and result rank"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_10","uri":"capability://data.processing.analysis.search.result.caching.and.deduplication.implicit","name":"search result caching and deduplication (implicit)","description":"While not explicitly documented, the architecture suggests potential for implementing result caching at the Crawler API level to avoid redundant searches for identical queries within a time window. The structured result format and centralized crawler enable future caching implementations without client-side changes, though current implementation likely lacks built-in caching or deduplication of results.","intents":["Reduce latency for repeated searches with identical queries","Decrease load on the Crawler API and external search engines","Improve cost efficiency by avoiding redundant search operations"],"best_for":["Applications with high search volume and repeated queries (e.g., FAQ bots, knowledge base search)","Teams running high-traffic AI agents where search latency is critical","Organizations with limited crawler resources that need to maximize throughput"],"limitations":["Current implementation likely has no caching — each search hits the crawler and search engine","No built-in cache invalidation strategy — stale results may be returned for time-sensitive queries","Cache key matching is exact query string only — similar queries with different formatting are not deduplicated","No distributed caching — each crawler instance maintains separate cache, limiting effectiveness in multi-instance deployments"],"requires":["Cache storage (in-memory, Redis, or similar) in Crawler API","Cache configuration (TTL, max size, eviction policy)","Mechanism to invalidate cache for time-sensitive queries"],"input_types":["search query string"],"output_types":["cached or fresh search results"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_2","uri":"capability://search.retrieval.parameterized.search.filtering.and.refinement","name":"parameterized search filtering and refinement","description":"Accepts multiple optional filter parameters (domain restrictions, language, region, excluded terms) that are passed through the MCP tool schema to the Crawler API, enabling fine-grained result filtering without requiring multiple sequential searches. Filters are applied server-side during result processing, reducing irrelevant results and improving search precision for domain-specific or localized queries.","intents":["Restrict search results to specific domains or domain groups to find information from trusted sources","Filter results by language or geographic region to get localized information","Exclude specific terms or domains to remove spam, ads, or irrelevant results from search output"],"best_for":["Developers building domain-specific AI agents that need to search only within trusted sources","Multi-language applications requiring region-specific or language-filtered search results","Teams filtering out spam domains or low-quality sources from search results"],"limitations":["Filters are applied post-search by the crawler — does not reduce API calls or network overhead","Domain filtering is string-based matching, not semantic — requires exact domain names or prefixes","No support for complex boolean queries (AND, OR, NOT) — only simple inclusion/exclusion lists","Language and region filters depend on crawler's ability to detect page language — may be inaccurate for multilingual content"],"requires":["WebSearch Crawler API with filter parameter support","Knowledge of target domains, language codes (ISO 639-1), and region codes for filtering"],"input_types":["domain_filter: comma-separated domain list or single domain","language: ISO 639-1 language code (e.g., 'en', 'fr', 'de')","region: region code for localized results","exclude_terms: comma-separated list of terms to exclude from results"],"output_types":["filtered JSON array of search results matching all specified filter criteria"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_3","uri":"capability://data.processing.analysis.structured.search.result.formatting.and.marshaling","name":"structured search result formatting and marshaling","description":"Transforms raw HTML search results from the Crawler API into a standardized JSON structure with title, snippet, URL, and metadata fields, then marshals this data through the MCP protocol to the client. The formatting layer ensures consistent result structure across different search sources and handles edge cases like missing fields or malformed HTML, providing clients with predictable, parseable output.","intents":["Receive search results in a consistent, structured format that can be reliably parsed by AI agents","Extract and normalize metadata (URLs, titles, snippets) from raw HTML search results","Ensure search results conform to a schema that MCP clients can validate and process"],"best_for":["AI agents and LLMs that need structured, predictable search result formats for reliable parsing","Developers building downstream processing pipelines that depend on consistent result schemas","Teams integrating search results into knowledge bases or vector databases that require normalized data"],"limitations":["Formatting adds ~50-100ms latency per search due to HTML parsing and JSON serialization","Snippet extraction is heuristic-based — may truncate important context or include irrelevant text","No deduplication of results — identical or near-duplicate results from different sources are returned separately","Metadata extraction depends on HTML structure — changes to search engine HTML layout may break parsing"],"requires":["WebSearch Crawler API returning raw HTML results","HTML parsing library (likely cheerio or similar) in the MCP server implementation"],"input_types":["raw HTML search results from Crawler API"],"output_types":["JSON array with objects containing: title (string), snippet (string), url (string), domain (string), rank (number)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_4","uri":"capability://automation.workflow.docker.containerized.self.hosted.deployment","name":"docker-containerized self-hosted deployment","description":"Packages the WebSearch Crawler API as a Docker container that can be deployed on-premises or in private infrastructure, eliminating dependency on third-party search engine APIs or cloud services. The container encapsulates the crawler logic, FlareSolverr integration, and HTTP server, enabling single-command deployment via Docker Compose or Kubernetes orchestration while maintaining full control over data and infrastructure.","intents":["Deploy web search infrastructure on-premises without relying on external search engine APIs","Avoid rate limits, IP bans, and usage quotas imposed by public search APIs","Maintain full control over search data and infrastructure for compliance or privacy requirements"],"best_for":["Enterprise teams requiring on-premises AI infrastructure with no external API dependencies","Organizations with strict data residency or privacy requirements preventing cloud search API usage","Teams building high-volume search applications that would exceed public API rate limits or quotas"],"limitations":["Requires Docker runtime and container orchestration expertise — adds operational overhead vs. serverless alternatives","Crawler container is stateless but CPU-intensive — requires significant compute resources for concurrent searches","No built-in horizontal scaling — requires manual Docker Compose or Kubernetes configuration for load balancing","FlareSolverr dependency adds another container to manage and monitor","Self-hosted crawler may be detected and blocked by anti-bot systems more easily than distributed cloud services"],"requires":["Docker 20.10+ or Docker Desktop","Docker Compose 1.29+ for multi-container deployment","2+ GB RAM and 2+ CPU cores for single crawler instance","Network access to public internet for web searches","FlareSolverr container running (separate Docker container)"],"input_types":["Docker image (websearch-mcp or custom build)","environment variables for configuration (API port, FlareSolverr endpoint, etc.)"],"output_types":["running Docker container exposing HTTP API on configured port"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_5","uri":"capability://tool.use.integration.mcp.server.npm.package.distribution","name":"mcp server npm package distribution","description":"Distributes the WebSearch-MCP server as an npm package (websearch-mcp) that developers can install via npm/yarn and configure in their MCP client setup files. The package includes pre-built TypeScript/JavaScript code, type definitions, and configuration templates, enabling rapid integration into Node.js-based MCP clients without requiring source compilation or manual setup.","intents":["Install WebSearch-MCP as a dependency in Node.js projects using standard npm package management","Integrate web search into Claude Desktop or other MCP clients via simple configuration file updates","Receive updates and bug fixes through standard npm versioning and update mechanisms"],"best_for":["Node.js developers building MCP-compatible applications who prefer npm-based dependency management","Teams using Claude Desktop or Cursor IDE that want to add web search via npm package installation","Developers who want to avoid Docker setup and prefer lightweight npm-based deployment"],"limitations":["Requires Node.js 16+ runtime — cannot be used in Python-only or non-Node.js environments","Still requires separate Docker Crawler API container — npm package only provides the MCP server wrapper","No pre-built binaries — requires Node.js runtime to execute, adding startup latency vs. compiled binaries","Package size and dependencies may be large — impacts installation time and disk usage"],"requires":["Node.js 16+ and npm/yarn package manager","WebSearch Crawler API running (Docker container or remote instance)","MCP client configuration file (claude_desktop_config.json or equivalent)"],"input_types":["npm install command","MCP client configuration JSON with server entry point"],"output_types":["installed npm package with executable MCP server entry point"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_6","uri":"capability://tool.use.integration.client.agnostic.mcp.protocol.abstraction","name":"client-agnostic mcp protocol abstraction","description":"Implements the MCP protocol layer as an abstraction that decouples the web search implementation from specific AI client details, enabling the same MCP server to work with Claude Desktop, Cursor, Cline, and any future MCP-compatible client without code changes. The server communicates via stdio transport using the standardized MCP message format, allowing clients to invoke the web_search tool through their native interfaces.","intents":["Use the same WebSearch-MCP server with multiple different MCP-compatible AI clients","Avoid vendor lock-in by implementing search capabilities through a standardized protocol","Enable future MCP clients to automatically support web search without requiring new server implementations"],"best_for":["Teams using multiple MCP-compatible clients (Claude Desktop, Cursor, Cline) that want unified search","Organizations standardizing on MCP protocol for tool orchestration across different AI platforms","Developers building MCP-compatible tools who want to support multiple clients simultaneously"],"limitations":["Requires all clients to support MCP protocol — non-MCP clients cannot use this server","Stdio transport limits communication to single process — cannot be used as a shared network service","MCP protocol overhead adds ~50-100ms latency per request compared to direct API calls","No built-in authentication or authorization — relies on client-side security and process isolation"],"requires":["MCP-compatible client with stdio transport support","MCP SDK or compatible library in the server implementation","Client configuration file pointing to the MCP server executable"],"input_types":["MCP protocol messages via stdin (tool call requests)"],"output_types":["MCP protocol messages via stdout (tool results, errors)"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_7","uri":"capability://tool.use.integration.configurable.crawler.api.endpoint.connectivity","name":"configurable crawler api endpoint connectivity","description":"Allows the MCP server to connect to a WebSearch Crawler API instance via configurable endpoint URL (local Docker container, remote server, or cloud deployment), enabling flexible deployment topologies. The server accepts the crawler endpoint as a configuration parameter, enabling users to point to different crawler instances without code changes, supporting both local development and distributed production deployments.","intents":["Connect the MCP server to a locally-running Crawler API container during development","Point the MCP server to a remote Crawler API instance in production or cloud environments","Switch between different Crawler API instances (e.g., for load balancing or failover) without redeploying the MCP server"],"best_for":["Teams deploying MCP server and Crawler API in separate containers or services","Organizations with distributed infrastructure requiring flexible endpoint configuration","Developers testing against multiple Crawler API instances or versions"],"limitations":["No built-in service discovery — requires manual endpoint configuration or environment variables","No automatic failover or load balancing — requires external orchestration (Kubernetes, Docker Compose) for HA","Network latency between MCP server and Crawler API adds to search latency — local deployment is faster","No connection pooling or keep-alive optimization — each search creates a new HTTP connection"],"requires":["WebSearch Crawler API running and accessible at configured endpoint","Network connectivity from MCP server to Crawler API (same network, VPN, or public internet)","Configuration mechanism (environment variables, config file, or command-line args) to specify endpoint"],"input_types":["crawler API endpoint URL (e.g., 'http://localhost:8000' or 'https://crawler.example.com')"],"output_types":["HTTP requests to Crawler API, receiving JSON search results"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_8","uri":"capability://tool.use.integration.request.response.flow.orchestration.through.mcp","name":"request-response flow orchestration through mcp","description":"Implements the complete request-response flow where the MCP server receives a tool invocation from the client, translates it into a Crawler API request, awaits the response, formats the results, and returns them through the MCP protocol. The orchestration layer handles error propagation, timeout management, and response marshaling, ensuring reliable end-to-end search execution from client invocation to result delivery.","intents":["Execute a complete web search from client request to formatted result delivery with proper error handling","Manage timeouts and failures during search execution without hanging the client","Ensure search results are properly formatted and returned through the MCP protocol"],"best_for":["Developers building reliable AI agents that need predictable search behavior with error handling","Teams requiring observability into search execution flow for debugging and monitoring","Applications that need timeout management to prevent hanging on slow or unresponsive crawlers"],"limitations":["Orchestration adds ~100-200ms overhead per search due to serialization and protocol handling","No built-in retry logic — failed searches require client-side retry implementation","Error messages are limited by MCP protocol — may not provide detailed debugging information","Timeout handling is basic — no exponential backoff or circuit breaker patterns"],"requires":["MCP SDK with tool invocation and result handling support","WebSearch Crawler API responding within reasonable timeout (e.g., 30 seconds)","Proper error handling in both MCP server and client"],"input_types":["MCP tool invocation with query and optional filter parameters"],"output_types":["MCP tool result with formatted search results or error message"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-websearch-mcp__cap_9","uri":"capability://automation.workflow.integration.with.flaresolverr.for.cloudflare.bypass","name":"integration with flaresolverr for cloudflare bypass","description":"The Crawler API integrates with FlareSolverr, a browser automation service that solves Cloudflare challenges and other anti-bot protections by rendering JavaScript and managing cookies. When the crawler encounters a protected site, it delegates the request to FlareSolverr, which returns the rendered HTML after bypassing protections, enabling searches on Cloudflare-protected domains that would otherwise be blocked.","intents":["Search websites protected by Cloudflare without being blocked or rate-limited","Access JavaScript-rendered content that requires browser automation to load","Bypass anti-bot protections that block simple HTTP requests"],"best_for":["Teams needing to search Cloudflare-protected websites from AI agents","Organizations running self-hosted search infrastructure that encounters protected domains","Developers building web scraping or search capabilities that must handle modern anti-bot systems"],"limitations":["FlareSolverr integration adds 2-5 second latency per protected site due to browser automation overhead","FlareSolverr must be running as separate Docker container — adds operational complexity","Browser automation is resource-intensive — limits concurrent protected site searches","Cloudflare may detect and block FlareSolverr traffic — requires ongoing maintenance as Cloudflare updates protections","Not all anti-bot systems are supported — only Cloudflare and similar JavaScript-based protections"],"requires":["FlareSolverr Docker container running and accessible to Crawler API","Network connectivity from Crawler API to FlareSolverr endpoint","Sufficient memory/CPU for browser automation (FlareSolverr is resource-intensive)"],"input_types":["HTTP request to protected website"],"output_types":["rendered HTML after Cloudflare challenge is solved"],"categories":["automation-workflow","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":27,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ (npm package distribution)","MCP-compatible client with stdio transport support","WebSearch Crawler API running and accessible (Docker container or remote instance)","Docker runtime for WebSearch Crawler API container","FlareSolverr container running and accessible to crawler (for Cloudflare bypass)","Network connectivity from MCP server to Crawler API endpoint","Sufficient memory/CPU for concurrent search requests (crawler is CPU-bound during rendering)","Cache storage (in-memory, Redis, or similar) in Crawler API","Cache configuration (TTL, max size, eviction policy)","Mechanism to invalidate cache for time-sensitive queries"],"failure_modes":["Requires MCP-compatible client — cannot be used with non-MCP AI assistants or APIs","Stdio transport adds latency for each search request — not suitable for high-frequency polling scenarios","No built-in caching or result deduplication across multiple identical search requests","FlareSolverr integration adds 2-5 second latency per search due to browser automation overhead","Crawler API must be running as separate Docker container — adds operational complexity vs. serverless alternatives","No built-in rate limiting or request queuing — high-volume searches may overwhelm the crawler instance","Search results depend on crawler's ability to parse HTML — JavaScript-heavy sites may return incomplete data","Current implementation likely has no caching — each search hits the crawler and search engine","No built-in cache invalidation strategy — stale results may be returned for time-sensitive queries","Cache key matching is exact query string only — similar queries with different formatting are not deduplicated","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.32,"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":"2026-06-17T09:51:04.689Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=websearch-mcp","compare_url":"https://unfragile.ai/compare?artifact=websearch-mcp"}},"signature":"uuhf5aJ4ScGFMeuF4Y0APHgCEvYAFEYFFK+xJnxqvF7sj48nAUMxgf0eQ8JmYg5hhcZfDy7hRD+pGHGZabjZDw==","signedAt":"2026-06-22T10:47:57.612Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/websearch-mcp","artifact":"https://unfragile.ai/websearch-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=websearch-mcp","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"}}