{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-metaphor","slug":"metaphor","name":"Metaphor","type":"model","url":"https://metaphor.systems/","page_url":"https://unfragile.ai/metaphor","categories":["research-search"],"tags":[],"pricing":{"model":"unknown","free":false,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-metaphor__cap_0","uri":"capability://search.retrieval.latency.optimized.web.search.with.configurable.speed.quality.tradeoff","name":"latency-optimized web search with configurable speed-quality tradeoff","description":"Executes web searches across a 70M+ company-indexed proprietary web crawl with four configurable latency profiles (instant <180ms, fast ~450ms, auto ~1s, deep 5-60s). Uses a custom ranking system optimized for AI query patterns rather than traditional SEO signals, returning results as JSON with URLs, titles, and snippets. The ranking model appears trained on relevance to LLM-based downstream tasks rather than human click-through data.","intents":["I need to search the web from within an AI agent with sub-500ms latency for real-time decision making","I want to trade off search speed for result quality depending on my use case (quick lookup vs deep research)","I need search results formatted as structured JSON for direct LLM consumption without parsing HTML"],"best_for":["AI agent developers building real-time research loops","LLM application builders needing web grounding with predictable latency SLAs","Teams building autonomous systems where search latency directly impacts response time"],"limitations":["Instant mode (<180ms) sacrifices result quality for speed; may miss relevant results in favor of indexed popularity","Index freshness varies by content type; not suitable for breaking news or real-time data not yet crawled","Cannot access paywalled, private, or authenticated content; limited to publicly indexed web","Deep search mode (5-60s) may exceed typical LLM context window timeouts in synchronous request patterns"],"requires":["API key from Exa (free tier: 1,000 requests/month)","HTTP client capable of REST API calls","Network connectivity to api.exa.ai"],"input_types":["natural language query string","optional structured parameters: num_results (1-10 base, up to 1,000 with enterprise), type filter (web|code|people|company|news), domain whitelist/blacklist"],"output_types":["JSON array of search results with: url, title, snippet, publishedDate (optional)","optional: full page contents (via Contents product)","optional: token-efficient highlights (excerpts)"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_1","uri":"capability://search.retrieval.deep.search.with.multi.step.reasoning.and.structured.output.extraction","name":"deep search with multi-step reasoning and structured output extraction","description":"Executes iterative, multi-step web research workflows that decompose complex queries into sub-queries, retrieve results for each step, and synthesize findings into structured JSON outputs. Uses an internal reasoning loop (likely LLM-based chain-of-thought) to determine follow-up searches and extract entities/relationships from results. Outputs are schema-flexible JSON suitable for downstream processing without additional parsing.","intents":["I need to research a complex topic (e.g., 'find all AI startups founded in 2023 in the Bay Area with Series A funding') that requires multiple search iterations","I want structured data extracted from web research (CEO names, founding dates, funding amounts) without manual parsing","I need to decompose a research task into sub-queries and synthesize results programmatically"],"best_for":["Data enrichment pipelines requiring web-sourced structured data","AI agents performing multi-step research tasks (competitive analysis, market research, due diligence)","Non-technical users building research workflows via API without writing custom parsing logic"],"limitations":["Deep search latency (5-60s) makes it unsuitable for real-time synchronous request patterns; best used in async/batch workflows","Structured output schema is not pre-defined; output format depends on query complexity and may vary across similar queries","Hallucination risk in synthesized outputs; no explicit citation mechanism to trace extracted data back to source URLs","Cost is higher ($12/1k requests vs $7/1k for standard search) and scales with number of sub-queries executed internally"],"requires":["API key from Exa","Async HTTP client or batch processing framework to handle 5-60s latency","JSON schema validation if strict output format is required"],"input_types":["natural language research query (e.g., 'find AI startups in SF with Series A funding')","optional: structured parameters for result filtering"],"output_types":["JSON object with extracted entities and relationships","structured fields vary by query (e.g., {companies: [{name, founded, funding, ceo}], sources: [urls]}"],"categories":["search-retrieval","planning-reasoning","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_10","uri":"capability://search.retrieval.domain.and.content.type.filtering.with.whitelist.blacklist","name":"domain and content-type filtering with whitelist/blacklist","description":"Allows search queries to be constrained by domain whitelist (search only specified domains) or blacklist (exclude specified domains), and by content type (e.g., exclude news, focus on documentation). Filtering is applied server-side during ranking, reducing irrelevant results before returning to client. Enables focused searches (e.g., 'search only GitHub and Stack Overflow' or 'exclude news and social media').","intents":["I want to search only specific domains (e.g., GitHub, Stack Overflow) without general web noise","I need to exclude certain content types (news, social media, ads) from search results","I want to focus search on documentation or technical content only"],"best_for":["Developer tool builders needing focused code/documentation search","Research applications requiring specific content sources","Applications where result quality is improved by domain constraints"],"limitations":["Whitelist/blacklist is domain-level only; cannot filter by subdomain or path","Content-type filtering options not fully documented; unclear what types are available","Filtering reduces result count; may return fewer than requested results if many are filtered","No regex or pattern-based filtering; only exact domain matching"],"requires":["API key from Exa","Knowledge of target domains for whitelist/blacklist"],"input_types":["domain whitelist array (e.g., ['github.com', 'stackoverflow.com'])","domain blacklist array (e.g., ['twitter.com', 'reddit.com'])","content-type filter parameter (format not documented)"],"output_types":["filtered search results from whitelisted domains or excluding blacklisted domains"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_11","uri":"capability://search.retrieval.real.time.web.indexing.with.configurable.crawl.freshness","name":"real-time web indexing with configurable crawl freshness","description":"Maintains a continuously-updated web index with configurable crawl frequency for different content types. News and frequently-updated content are crawled more frequently; static documentation less frequently. Enables searches to return recently-published content (e.g., news articles, blog posts) without waiting for manual re-indexing. Crawl freshness is not user-configurable but varies by content type and source authority.","intents":["I need search results that include recently-published content (news, blog posts) without stale results","I want to monitor for new research papers or articles on a topic and have them appear in search within hours","I need to track breaking news or product announcements as they are published"],"best_for":["News aggregation and monitoring applications","Research tracking systems requiring recent publications","Competitive intelligence platforms needing timely updates"],"limitations":["Crawl freshness is not user-configurable; determined by Exa's internal policies","Breaking news may have 1-24 hour lag before appearing in index (exact SLA not documented)","Crawl frequency varies by content type and source; no transparency into which sources are crawled when","Real-time indexing adds infrastructure cost; may impact search latency for some queries"],"requires":["API key from Exa","Acceptance that crawl freshness is Exa-managed, not user-configurable"],"input_types":["standard search query"],"output_types":["search results including recently-indexed content with publishedDate metadata"],"categories":["search-retrieval","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_2","uri":"capability://search.retrieval.specialized.vertical.search.with.domain.specific.indexes","name":"specialized vertical search with domain-specific indexes","description":"Provides dedicated search indexes optimized for specific content verticals: code (GitHub, Stack Overflow, documentation), people (professional profiles, bios), companies (structured company data with fields like founding year, CEO, funding), news (news-specific ranking), and general web. Each vertical uses domain-specific ranking signals and structured metadata extraction tailored to that content type. Queries can specify a vertical via type parameter to constrain search scope.","intents":["I need to search GitHub repositories and Stack Overflow for code solutions without general web noise","I want to find people by name/role with professional context (e.g., 'find CTOs at AI startups')","I need structured company data (CEO, founding year, funding) extracted from web sources without manual research"],"best_for":["Developer tool builders integrating code search (IDE plugins, code review tools)","Recruitment/HR platforms needing people search with professional context","Business intelligence and market research tools requiring structured company data","News aggregation and monitoring systems"],"limitations":["Code vertical limited to publicly indexed repositories; private/enterprise code not accessible","People vertical may have incomplete or outdated professional information; no real-time profile updates","Company data accuracy depends on web source quality; may contain outdated or conflicting information across sources","News vertical latency depends on crawl frequency; breaking news may not appear immediately","Vertical selection is mutually exclusive; cannot search across multiple verticals in a single query"],"requires":["API key from Exa","Knowledge of which vertical is appropriate for the query (type parameter: web|code|people|company|news)"],"input_types":["natural language query optimized for the vertical (e.g., 'React hooks tutorial' for code, 'CTO at OpenAI' for people)","type parameter specifying vertical"],"output_types":["code vertical: repository URLs, file paths, code snippets, documentation links","people vertical: profile URLs, names, titles, company affiliations","company vertical: company name, CEO, founding year, funding stage, industry, structured fields","news vertical: article URLs, headlines, publication dates, news sources","general web: standard search results"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_3","uri":"capability://memory.knowledge.token.efficient.page.content.retrieval.with.highlights","name":"token-efficient page content retrieval with highlights","description":"Retrieves full HTML/text content of web pages indexed by Exa and optionally generates token-efficient highlights (key excerpts) that summarize page content without requiring full page processing by downstream LLMs. Highlights are pre-computed during indexing and returned as a separate field, reducing token consumption for LLM processing. Full contents are returned as raw text suitable for RAG pipelines or LLM context windows.","intents":["I need to retrieve full page content for a URL without making separate HTTP requests to the target site","I want to reduce LLM token consumption by using pre-computed highlights instead of full page text","I need to build a RAG pipeline that chunks and embeds web content without external HTML parsing libraries"],"best_for":["RAG (Retrieval-Augmented Generation) pipeline builders needing efficient content retrieval","LLM application developers optimizing token usage and cost","Web scraping automation where target sites block direct access or have rate limits"],"limitations":["Full page contents may include boilerplate (navigation, ads, footers) not filtered out; requires downstream cleaning for optimal LLM input","Highlights are pre-computed and may not align with specific downstream use cases; custom summarization may be needed","Content freshness depends on crawl frequency; stale pages may be returned if not recently re-indexed","Pricing is per-page ($1/1k pages); retrieving contents for 100 search results costs $0.10 per search, adding significant cost at scale","No support for JavaScript-rendered content; only static HTML indexed"],"requires":["API key from Exa","Contents product enabled (separate pricing tier)"],"input_types":["URL string (from prior search results or external source)"],"output_types":["full page text content (raw HTML or plaintext)","optional: highlights array (key excerpts as strings)","optional: token count estimate for highlights"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_4","uri":"capability://automation.workflow.web.event.monitoring.with.configurable.cadence","name":"web event monitoring with configurable cadence","description":"Sets up persistent monitors that track changes to specified web pages or search queries at configurable intervals (daily, weekly, or custom). When changes are detected, returns new/updated content matching the monitor criteria. Internally maintains a state machine tracking page versions and diffs, triggering notifications when content changes exceed a threshold. Useful for tracking competitor websites, news about specific topics, or monitoring for new research publications.","intents":["I want to monitor a competitor's website for pricing or feature changes without manual daily checks","I need to track new research papers or blog posts on a specific topic and be notified when they appear","I want to set up alerts for mentions of my company or product across the web"],"best_for":["Competitive intelligence platforms","Research monitoring systems (academic papers, preprints, blog posts)","Brand monitoring and reputation management tools","Market intelligence and trend tracking applications"],"limitations":["Monitors are query-based, not URL-based; cannot monitor arbitrary URLs outside Exa's index","Change detection sensitivity is not configurable; threshold for 'change detected' is opaque","Cadence is limited to predefined intervals (daily/weekly); sub-daily monitoring not available","Pricing ($15/1k requests) is higher than standard search; cost scales with number of monitors and check frequency","No webhook/push notification support; polling-based retrieval only (must call API to check for updates)"],"requires":["API key from Exa","Monitors product enabled"],"input_types":["search query string to monitor","cadence parameter (daily, weekly, or custom interval)","optional: result count and filtering parameters"],"output_types":["array of new/updated search results since last check","timestamp of last check","change detection metadata (if available)"],"categories":["automation-workflow","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_5","uri":"capability://text.generation.language.web.grounded.answer.generation.with.streaming.responses","name":"web-grounded answer generation with streaming responses","description":"Generates natural language answers to queries by first retrieving relevant web content via search, then using an internal LLM to synthesize answers grounded in retrieved sources. Supports streaming responses for progressive answer delivery. Internally chains search → retrieval → LLM generation, with optional citation of source URLs. Answers are streamed token-by-token, enabling real-time display in user interfaces.","intents":["I want to provide users with web-grounded answers without building my own search + LLM pipeline","I need streaming answer generation for real-time UI updates while research is in progress","I want answers with source citations so users can verify claims"],"best_for":["Chatbot and conversational AI builders needing web-grounded responses","Search-augmented LLM applications (search + synthesis in one API call)","Real-time answer generation interfaces where streaming is critical for UX"],"limitations":["Answer quality depends on search result quality; poor search results lead to poor answers","No explicit hallucination detection or confidence scoring; answers may contain unsupported claims","Citation mechanism is not transparent; unclear how sources are selected and attributed","Streaming adds latency overhead; total time-to-first-token may be higher than non-streaming search","Internal LLM model is not specified; no control over model selection or temperature/parameters","Pricing ($5/1k requests) is separate from search; total cost is search + answer generation"],"requires":["API key from Exa","Answer product enabled","HTTP client supporting streaming responses (Server-Sent Events or chunked transfer encoding)"],"input_types":["natural language query string"],"output_types":["streaming text response (token-by-token via SSE or chunked encoding)","optional: source URLs and citations (format unclear from documentation)","optional: structured metadata (confidence, sources used, etc. — not documented)"],"categories":["text-generation-language","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_6","uri":"capability://tool.use.integration.native.tool.calling.integration.with.major.llm.providers","name":"native tool calling integration with major llm providers","description":"Provides pre-built function calling schemas compatible with OpenAI, Anthropic, and other LLM providers' native tool-calling APIs. Exa search functions are registered as tools that LLMs can invoke directly, with automatic parameter marshaling and response formatting. Integrates with LangChain, LlamaIndex, CrewAI, and Vercel AI SDK for seamless agent integration without custom wrapper code.","intents":["I want my LLM agent to call Exa search as a native tool without writing custom function definitions","I need Exa search integrated into my LangChain/LlamaIndex agent with minimal boilerplate","I want to use Exa with Anthropic's tool_use or OpenAI's function_calling without manual schema definition"],"best_for":["LLM agent developers using OpenAI, Anthropic, or other tool-calling-compatible models","Teams building with LangChain, LlamaIndex, CrewAI, or Vercel AI SDK","Developers wanting to minimize integration boilerplate and focus on agent logic"],"limitations":["Tool calling adds latency overhead (LLM must decide to call tool, then tool executes); not suitable for sub-100ms response requirements","LLM may hallucinate tool parameters or misuse search; requires guardrails or prompt engineering to ensure correct usage","Tool calling is stateless; no built-in memory of previous searches within a conversation (requires external state management)","Integration quality depends on SDK/framework version; breaking changes in LLM provider APIs may require updates"],"requires":["API key from Exa","API key for LLM provider (OpenAI, Anthropic, etc.)","SDK for integration framework (langchain, llamaindex, crewai, vercel-ai, etc.)","Python 3.9+ or Node.js 18+ depending on SDK"],"input_types":["LLM-generated tool call with parameters: query (string), num_results (int), type (string), etc."],"output_types":["formatted tool response: search results as JSON, ready for LLM consumption"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_7","uri":"capability://data.processing.analysis.enterprise.custom.indexing.and.zero.data.retention.compliance","name":"enterprise custom indexing and zero-data-retention compliance","description":"Provides enterprise customers with ability to create custom web indexes (e.g., internal documentation, proprietary data sources) and configure data retention policies including Zero Data Retention (ZDR) where queries and results are automatically purged after processing. Enables compliance with data privacy regulations (GDPR, HIPAA) and security requirements. Custom indexes are maintained separately from public web index and can be restricted to authorized users.","intents":["I need to search internal documentation or proprietary data sources without exposing them to public web index","I require Zero Data Retention for compliance (GDPR, HIPAA) where queries cannot be logged or retained","I want to restrict search access to specific data sources for security or licensing reasons"],"best_for":["Enterprise organizations with compliance requirements (GDPR, HIPAA, SOC 2)","Teams handling sensitive data (healthcare, finance, legal) requiring data retention controls","Organizations with proprietary knowledge bases or internal documentation needing search"],"limitations":["Custom indexing requires enterprise contract and 1:1 onboarding; not available on standard pricing tiers","ZDR may add latency overhead (data purging operations); exact impact not documented","Custom index maintenance is Exa's responsibility; no control over crawl frequency or index refresh","Pricing for custom indexes is not publicly disclosed; requires enterprise negotiation","No self-service custom index creation; requires Exa support involvement"],"requires":["Enterprise contract with Exa","1:1 onboarding and support engagement","Data source access (URLs, APIs, or data feeds for indexing)"],"input_types":["custom data sources (URLs, documentation, data feeds) for indexing","data retention policy configuration (ZDR or custom retention periods)"],"output_types":["custom index with search results scoped to provided data sources","audit logs confirming data purging (if ZDR enabled)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_8","uri":"capability://tool.use.integration.mcp.model.context.protocol.server.integration.for.claude.and.compatible.clients","name":"mcp (model context protocol) server integration for claude and compatible clients","description":"Implements Exa search as an MCP server, enabling Claude (and other MCP-compatible clients) to invoke Exa search natively without custom tool definitions. MCP is a standardized protocol for LLM-to-tool communication, allowing Claude to discover and call Exa search functions as if they were built-in capabilities. Requires running an MCP server process that bridges Claude's requests to Exa API.","intents":["I want Claude to search the web natively without custom tool definitions or wrapper code","I need to use Exa search with Claude Desktop or other MCP-compatible clients","I want standardized tool communication via MCP instead of provider-specific tool calling APIs"],"best_for":["Claude users and developers building Claude-based applications","Teams standardizing on MCP for tool integration across multiple LLMs","Developers wanting to avoid provider-specific tool calling syntax (OpenAI vs Anthropic)"],"limitations":["Requires running a separate MCP server process; adds deployment complexity vs. direct API calls","MCP is a newer standard; adoption and stability may be lower than established tool calling APIs","MCP server implementation details (latency, error handling) not documented","Limited to MCP-compatible clients (Claude, some open-source LLMs); not compatible with OpenAI or Anthropic native APIs directly"],"requires":["API key from Exa","MCP server runtime (Python or Node.js)","Claude Desktop or MCP-compatible LLM client","Network connectivity between MCP server and Exa API"],"input_types":["MCP tool call from Claude with search parameters"],"output_types":["MCP tool response with search results formatted for Claude"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-metaphor__cap_9","uri":"capability://data.processing.analysis.batch.processing.and.bulk.search.with.volume.discounts","name":"batch processing and bulk search with volume discounts","description":"Supports batch submission of multiple search queries in a single API call, with per-request pricing that decreases at volume (e.g., $7/1k requests at standard tier, lower rates for enterprise). Enables cost-efficient bulk research workflows where hundreds or thousands of searches are executed asynchronously. Results are returned as an array, suitable for data pipeline processing.","intents":["I need to run 1,000+ searches for data enrichment (e.g., company research, competitor analysis) and want volume discounts","I want to batch multiple search queries into a single API call for efficiency","I need to process search results in bulk without per-query overhead"],"best_for":["Data enrichment and ETL pipelines processing large datasets","Batch research workflows (competitive analysis, market research, due diligence)","Organizations with high search volume (1,000+ queries/month) seeking cost optimization"],"limitations":["Batch API details not documented; unclear if batches are processed sequentially or in parallel","No explicit SLA for batch processing latency; may be slower than individual requests","Volume discounts require enterprise contract; standard tier pricing is fixed","Batch size limits not specified; may have maximum queries per batch","No built-in retry or error handling for partial batch failures; unclear how failed queries are reported"],"requires":["API key from Exa","Batch processing capability (likely requires enterprise tier)"],"input_types":["array of search query objects with parameters"],"output_types":["array of search result arrays (one per input query)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":22,"verified":false,"data_access_risk":"high","permissions":["API key from Exa (free tier: 1,000 requests/month)","HTTP client capable of REST API calls","Network connectivity to api.exa.ai","API key from Exa","Async HTTP client or batch processing framework to handle 5-60s latency","JSON schema validation if strict output format is required","Knowledge of target domains for whitelist/blacklist","Acceptance that crawl freshness is Exa-managed, not user-configurable","Knowledge of which vertical is appropriate for the query (type parameter: web|code|people|company|news)","Contents product enabled (separate pricing tier)"],"failure_modes":["Instant mode (<180ms) sacrifices result quality for speed; may miss relevant results in favor of indexed popularity","Index freshness varies by content type; not suitable for breaking news or real-time data not yet crawled","Cannot access paywalled, private, or authenticated content; limited to publicly indexed web","Deep search mode (5-60s) may exceed typical LLM context window timeouts in synchronous request patterns","Deep search latency (5-60s) makes it unsuitable for real-time synchronous request patterns; best used in async/batch workflows","Structured output schema is not pre-defined; output format depends on query complexity and may vary across similar queries","Hallucination risk in synthesized outputs; no explicit citation mechanism to trace extracted data back to source URLs","Cost is higher ($12/1k requests vs $7/1k for standard search) and scales with number of sub-queries executed internally","Whitelist/blacklist is domain-level only; cannot filter by subdomain or path","Content-type filtering options not fully documented; unclear what types are available","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.34,"ecosystem":0.25,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:03.578Z","last_scraped_at":"2026-05-03T14:00:23.056Z","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=metaphor","compare_url":"https://unfragile.ai/compare?artifact=metaphor"}},"signature":"A72DQvzCnCS95dv6T/sOt8cK6cnCTcM7Kui/FMlNPnmM5YxpCwvIO+76CZu5qy5Bthhm75gyQDXs5sF4KTyyBA==","signedAt":"2026-06-21T15:51:39.944Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/metaphor","artifact":"https://unfragile.ai/metaphor","verify":"https://unfragile.ai/api/v1/verify?slug=metaphor","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"}}