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The MCP server translates search queries into Tavily API calls, handling authentication via API keys and formatting responses as structured JSON for consumption by Claude and other MCP clients. Results are ranked by relevance rather than raw PageRank, prioritizing content quality for LLM reasoning.","intents":["I need to search the web and get current information to answer a user question in real-time","I want to augment my LLM's knowledge with live web data without building my own search infrastructure","I need to retrieve multiple relevant sources quickly to fact-check or validate claims"],"best_for":["AI agents and chatbots needing real-time information access","Claude Desktop users wanting integrated web search without plugins","Teams building MCP-compatible applications requiring search capabilities"],"limitations":["Requires valid Tavily API key with active subscription or free tier limits","Search results depend on Tavily's index freshness and crawler coverage","No built-in caching — repeated identical queries incur API costs","Rate limiting applies based on Tavily subscription tier"],"requires":["Tavily API key (free tier available)","Node.js 14+ for running the MCP server","MCP-compatible client (Claude Desktop, custom MCP host, etc.)","Network connectivity to Tavily API endpoints"],"input_types":["text (search query string)"],"output_types":["structured JSON with search results array","fields: title, url, snippet, relevance_score"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_1","uri":"capability://data.processing.analysis.web.page.content.extraction.and.summarization","name":"web page content extraction and summarization","description":"Extracts full-text content from web pages and optionally generates summaries using Tavily's extraction engine. The MCP server accepts a URL, fetches the page via Tavily's crawler (handling JavaScript rendering, redirects, and content parsing), and returns cleaned HTML or markdown with metadata (title, author, publish date). Supports optional AI-powered summarization to reduce token consumption for long documents.","intents":["I found a relevant URL in search results but need the full content to analyze it","I want to extract structured data from a web page without writing a custom scraper","I need to summarize a long article to fit it into my LLM's context window"],"best_for":["Agents performing multi-step research workflows (search → extract → analyze)","Document processing pipelines that need to handle arbitrary web content","RAG systems building knowledge bases from live web sources"],"limitations":["Extraction quality depends on page structure and Tavily's parser heuristics","JavaScript-heavy SPAs may not render correctly without explicit configuration","Large pages (>10MB) may be truncated or fail extraction","No support for authenticated/paywalled content","Extraction adds latency (typically 2-5 seconds per page)"],"requires":["Tavily API key with extraction capability enabled","Valid, publicly accessible URL","Network connectivity to Tavily extraction service"],"input_types":["text (URL string)","optional: boolean flag for summarization"],"output_types":["structured JSON with extracted content","fields: raw_content, markdown, title, author, publish_date, summary (optional)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_2","uri":"capability://tool.use.integration.mcp.tool.registration.and.schema.binding","name":"mcp tool registration and schema binding","description":"Registers Tavily search and extraction capabilities as MCP tools with JSON Schema definitions, enabling Claude and other MCP clients to discover and invoke them with type-safe parameters. The server implements the MCP tool protocol, exposing tool definitions (name, description, input schema) that clients use to generate UI and validate arguments before execution. Handles parameter marshaling, error responses, and result formatting according to MCP specification.","intents":["I want Claude to automatically use web search when it needs current information","I need to expose search and extraction as discoverable tools in my MCP-compatible application","I want type validation and schema enforcement for search parameters before API calls"],"best_for":["Claude Desktop users configuring MCP servers","Developers building custom MCP hosts or agents","Teams standardizing on MCP for tool integration across multiple LLM applications"],"limitations":["Requires MCP-compatible client — not compatible with standard REST APIs or OpenAI function calling","Tool discovery is static at server startup — adding new tools requires server restart","Schema validation is basic JSON Schema — no custom validation logic per parameter","Error handling relies on client's MCP error handling implementation"],"requires":["MCP client library or compatible application (Claude Desktop, custom host)","Node.js 14+ for running the server","Understanding of MCP protocol and tool schema format"],"input_types":["MCP tool call requests with JSON parameters"],"output_types":["MCP tool response with structured result or error"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_3","uri":"capability://tool.use.integration.claude.desktop.integration.with.automatic.tool.discovery","name":"claude desktop integration with automatic tool discovery","description":"Configures the MCP server to run as a subprocess managed by Claude Desktop, with automatic tool discovery on startup. Claude Desktop reads the server configuration, spawns the Node.js process, and establishes a bidirectional stdio-based communication channel. Tools are discovered via the MCP list_tools protocol, making search and extraction available in Claude's interface without manual setup.","intents":["I want to use web search in Claude Desktop without installing a plugin","I need to configure Claude to automatically search the web when answering questions","I want to set up a local MCP server that Claude can call without cloud dependencies"],"best_for":["Claude Desktop users wanting native web search integration","Teams deploying MCP servers in local/private environments","Developers prototyping MCP-based agent architectures"],"limitations":["Requires Claude Desktop application (not available for Claude web interface)","Server runs as a local subprocess — no horizontal scaling or load balancing","Configuration requires editing Claude's config file (JSON) — not GUI-based","Server lifecycle tied to Claude Desktop process — crashes require manual restart","No built-in monitoring or logging beyond Claude's debug console"],"requires":["Claude Desktop application (latest version recommended)","Node.js 14+ installed and in system PATH","Access to Claude's configuration directory (~/.claude/)","Tavily API key configured as environment variable or in config"],"input_types":["MCP server configuration (JSON)"],"output_types":["Tool availability in Claude Desktop interface"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_4","uri":"capability://search.retrieval.parameterized.search.with.query.refinement","name":"parameterized search with query refinement","description":"Accepts search queries with optional parameters (topic, search_depth, include_domains, exclude_domains) to refine results. The MCP server translates these parameters into Tavily API query options, enabling users to constrain searches by domain, depth (basic vs comprehensive), and topic context. Supports negative filtering (exclude_domains) to remove irrelevant sources and positive filtering (include_domains) to prioritize trusted sources.","intents":["I want to search only within specific domains (e.g., academic papers, news sites)","I need to exclude spam or low-quality sources from my search results","I want to do a deep search with more results for comprehensive research"],"best_for":["Researchers needing domain-specific search (academic, news, technical docs)","Agents filtering out unreliable sources programmatically","Applications requiring fine-grained control over search scope"],"limitations":["Domain filtering is prefix-based — no regex or wildcard support","Search depth (basic vs comprehensive) affects API cost and latency","Topic parameter is advisory only — not guaranteed to filter results","No support for date range filtering or language-specific search"],"requires":["Tavily API key","Understanding of domain names for include/exclude filters"],"input_types":["text (query string)","string (topic, optional)","string array (include_domains, optional)","string array (exclude_domains, optional)","enum (search_depth: 'basic' | 'comprehensive', optional)"],"output_types":["structured JSON with filtered search results"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_5","uri":"capability://automation.workflow.error.handling.and.api.failure.recovery","name":"error handling and api failure recovery","description":"Implements retry logic and graceful error handling for Tavily API failures, network timeouts, and invalid parameters. The server catches API errors (rate limits, invalid keys, malformed queries), translates them into MCP error responses with human-readable messages, and optionally retries transient failures (network timeouts, 5xx errors) with exponential backoff. Invalid parameters are rejected with schema validation errors before API calls.","intents":["I want my agent to handle search failures gracefully without crashing","I need to know why a search failed (rate limit, invalid key, network error)","I want automatic retry for transient failures without manual intervention"],"best_for":["Production agents requiring reliability and observability","Applications with strict uptime requirements","Teams debugging integration issues with clear error messages"],"limitations":["Retry logic only applies to transient errors (5xx, timeouts) — not permanent failures (invalid key, 403)","Exponential backoff may delay responses for slow networks","No circuit breaker pattern — repeated failures don't trigger fallback behavior","Error messages are limited to Tavily API responses — no custom error context"],"requires":["Tavily API key (for authentication errors)","Network connectivity (for timeout handling)"],"input_types":["any search or extraction request"],"output_types":["MCP error response with error code and message","fields: error_code, error_message, retry_after (optional)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_6","uri":"capability://safety.moderation.environment.based.api.key.management","name":"environment-based api key management","description":"Reads Tavily API key from environment variables (TAVILY_API_KEY) at server startup, eliminating the need to hardcode credentials in configuration files. The server validates the API key format on initialization and fails fast if the key is missing or invalid, preventing runtime errors during tool execution. Supports both local development (via .env files) and production deployment (via system environment variables).","intents":["I want to configure my API key securely without storing it in code or config files","I need to deploy the MCP server in different environments with different API keys","I want the server to fail fast if the API key is missing or invalid"],"best_for":["Teams following security best practices for credential management","CI/CD pipelines deploying MCP servers to multiple environments","Local development workflows using .env files"],"limitations":["API key must be set before server startup — no runtime key rotation","No support for key expiration or automatic refresh","Environment variable names are fixed (TAVILY_API_KEY) — no customization","No built-in encryption for environment variables — relies on OS-level security"],"requires":["TAVILY_API_KEY environment variable set","Valid Tavily API key format"],"input_types":["environment variable (string)"],"output_types":["validated API key (used internally for all API calls)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-tavily-mcp__cap_7","uri":"capability://data.processing.analysis.structured.result.formatting.for.llm.consumption","name":"structured result formatting for llm consumption","description":"Formats search results and extracted content as structured JSON optimized for LLM reasoning, including relevance scores, source metadata, and content snippets. The server normalizes Tavily API responses into a consistent schema with fields like title, url, snippet, relevance_score, and publish_date, enabling Claude and other LLMs to reason about source quality and recency. Markdown formatting is applied to extracted content for readability.","intents":["I want search results formatted in a way that Claude can easily reason about","I need to include source metadata (URL, publish date) in my LLM's reasoning","I want extracted content formatted as markdown for readability in the LLM context"],"best_for":["LLM agents needing structured data for reasoning and citation","Applications building knowledge bases from web sources","Teams standardizing on consistent result formats across multiple search tools"],"limitations":["Schema is fixed — no customization for application-specific fields","Relevance scores are Tavily's proprietary algorithm — not transparent","Markdown formatting may lose some HTML structure (tables, complex layouts)","No support for custom field mapping or schema transformation"],"requires":["Tavily API key"],"input_types":["Tavily API response (JSON)"],"output_types":["structured JSON with normalized fields","fields: title, url, snippet, relevance_score, publish_date, content (for extraction)"],"categories":["data-processing-analysis","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":43,"verified":false,"data_access_risk":"high","permissions":["Tavily API key (free tier available)","Node.js 14+ for running the MCP server","MCP-compatible client (Claude Desktop, custom MCP host, etc.)","Network connectivity to Tavily API endpoints","Tavily API key with extraction capability enabled","Valid, publicly accessible URL","Network connectivity to Tavily extraction service","MCP client library or compatible application (Claude Desktop, custom host)","Node.js 14+ for running the server","Understanding of MCP protocol and tool schema format"],"failure_modes":["Requires valid Tavily API key with active subscription or free tier limits","Search results depend on Tavily's index freshness and crawler coverage","No built-in caching — repeated identical queries incur API costs","Rate limiting applies based on Tavily subscription tier","Extraction quality depends on page structure and Tavily's parser heuristics","JavaScript-heavy SPAs may not render correctly without explicit configuration","Large pages (>10MB) may be truncated or fail extraction","No support for authenticated/paywalled content","Extraction adds latency (typically 2-5 seconds per page)","Requires MCP-compatible client — not compatible with standard REST APIs or OpenAI function calling","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.6312346896628672,"quality":0.26,"ecosystem":0.6000000000000001,"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":"2026-05-24T12:16:23.902Z","last_scraped_at":"2026-05-03T14:04:47.472Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":71638,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=tavily-mcp","compare_url":"https://unfragile.ai/compare?artifact=tavily-mcp"}},"signature":"uZoTLnegijY3XynYt7iaUb/AdRlwGZOwhIy74EJgo9Ql0g9difrqGZlmATesfE7ZrB5c1E7hplckpfWgXREoBA==","signedAt":"2026-06-20T20:24:28.333Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/tavily-mcp","artifact":"https://unfragile.ai/tavily-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=tavily-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"}}