{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"exa-mcp-server","slug":"exa-mcp-server","name":"Exa MCP Server","type":"mcp","url":"https://github.com/exa-labs/exa-mcp-server","page_url":"https://unfragile.ai/exa-mcp-server","categories":["mcp-servers","rag-knowledge"],"tags":["exa","search","neural","official"],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"exa-mcp-server__cap_0","uri":"capability://search.retrieval.semantic.web.search.with.neural.ranking","name":"semantic web search with neural ranking","description":"Executes semantic web searches using Exa's neural search index, which ranks results by semantic relevance rather than keyword matching. The server translates natural language queries into vector embeddings via the Exa API, retrieves ranked results with metadata (URL, title, snippet, publication date), and returns structured JSON with configurable result limits. This differs from traditional keyword-based search by understanding query intent and returning contextually relevant pages even without exact keyword matches.","intents":["I need to find recent articles about a specific topic without knowing exact keywords","I want search results ranked by relevance to my research question, not just keyword frequency","I need to integrate real-time web search into my AI agent with minimal latency"],"best_for":["AI agents and LLM applications requiring real-time web context","Research assistants needing semantic understanding of search intent","Teams building RAG systems that need fresh, ranked web content"],"limitations":["Requires valid Exa API key with active quota; free tier has rate limits","Results depend on Exa's index freshness; very new content may not be indexed","Cannot search within password-protected or dynamically-rendered content","Semantic ranking may return unexpected results for highly technical or niche queries"],"requires":["Exa API key (free tier available)","MCP client compatible with stdio or HTTP/SSE transport","Node.js 16+ for local deployment"],"input_types":["text (natural language query string)"],"output_types":["JSON array of search results with URL, title, snippet, published date, score"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_1","uri":"capability://search.retrieval.full.page.content.retrieval.with.html.to.text.conversion","name":"full-page content retrieval with html-to-text conversion","description":"Fetches complete page content from a given URL and automatically converts HTML to clean, readable text suitable for LLM consumption. The server handles DOM parsing, removes boilerplate (navigation, ads, scripts), extracts main content, and returns structured text with preserved formatting. This replaces traditional web crawling by providing AI-ready content without manual parsing or regex-based extraction.","intents":["I need to extract the full text content from a specific webpage for my AI to analyze","I want to avoid parsing HTML manually and get clean, LLM-ready text from a URL","I need to retrieve article content without dealing with ads, navigation menus, or tracking code"],"best_for":["RAG pipelines that need fresh web content ingestion","AI agents performing detailed analysis of specific web pages","Researchers building knowledge bases from web sources"],"limitations":["Cannot fetch content from pages requiring JavaScript execution or authentication","Respects robots.txt and may fail on sites with strict crawling restrictions","Large pages (>10MB) may be truncated or timeout","Dynamic content loaded after page render is not captured"],"requires":["Exa API key with web_fetch_exa tool enabled","Valid, publicly accessible URL","MCP client with tool invocation support"],"input_types":["text (URL string)"],"output_types":["text (cleaned HTML-to-text conversion with metadata)"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_10","uri":"capability://automation.workflow.request.lifecycle.management.with.timeout.and.quota.handling","name":"request lifecycle management with timeout and quota handling","description":"Manages the complete lifecycle of Exa API requests, including timeout handling, rate limit detection, and quota enforcement. The server monitors request duration, detects Exa API rate limit responses (429 status), and returns meaningful error messages to clients. This enables graceful degradation under load and prevents clients from overwhelming the Exa API with requests.","intents":["I want my agent to handle rate limits gracefully instead of crashing when the API quota is exceeded","I need to understand when my Exa API quota is exhausted and plan accordingly","I want to set timeouts on search requests to prevent hanging indefinitely"],"best_for":["Production deployments with multiple clients sharing a single API key","High-traffic MCP servers where rate limiting is a concern","Teams monitoring API quota usage and planning capacity"],"limitations":["Timeout handling is transport-specific — stdio, HTTP/SSE, and serverless have different timeout semantics","Rate limit detection is reactive — server detects 429 responses after the request is made, not before","No built-in quota tracking or predictive rate limiting — cannot warn clients before quota is exhausted","Timeout values are hardcoded or configured globally — no per-tool or per-client timeout customization","Quota information is not exposed to clients — clients cannot query remaining quota before making requests"],"requires":["Exa API key with known quota limits","Timeout configuration (likely in environment variables or config file)","Client-side retry logic to handle rate limit responses"],"input_types":["Exa API request with timeout configuration"],"output_types":["Exa API response or timeout/rate limit error"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_2","uri":"capability://search.retrieval.advanced.search.with.granular.filtering.and.domain.constraints","name":"advanced search with granular filtering and domain constraints","description":"Provides fine-grained control over search parameters including domain whitelisting/blacklisting, date range filtering, content category filtering, and result type specification (news, research papers, etc.). The server accepts structured filter objects and translates them into Exa API query parameters, enabling researchers to narrow results to specific sources, time periods, or content types. This is an opt-in tool for use cases requiring precision over breadth.","intents":["I need to search only within academic papers or news articles from the past 6 months","I want to exclude certain domains or restrict results to a whitelist of trusted sources","I need to find content in specific categories (e.g., research, news, blogs) with date constraints"],"best_for":["Researchers requiring domain-specific or time-bounded searches","Compliance-focused applications needing source verification","Specialized agents (news aggregators, academic research tools) with strict filtering needs"],"limitations":["Requires knowledge of Exa's supported categories and filter syntax; not all filters are available on free tier","Date filtering depends on Exa's metadata extraction; some pages may lack reliable publish dates","Domain whitelisting can be overly restrictive and reduce result diversity","Complex filter combinations may reduce result count significantly"],"requires":["Exa API key (some filters require paid tier)","Understanding of filter parameter structure (domains, startPublishedDate, endPublishedDate, category)","MCP client supporting tool invocation with structured parameters"],"input_types":["text (query string)","JSON object (filter configuration with domains, dates, categories)"],"output_types":["JSON array of filtered search results with applied constraints metadata"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_3","uri":"capability://tool.use.integration.mcp.protocol.bridging.with.multi.transport.deployment","name":"mcp protocol bridging with multi-transport deployment","description":"Implements the Model Context Protocol (MCP) specification to expose Exa tools as callable functions within MCP-compatible clients (Claude, VS Code, Cursor, etc.). The server supports multiple transport mechanisms: stdio for local deployment, HTTP/SSE for hosted endpoints, and serverless functions (Vercel). A single codebase (src/mcp-handler.ts) defines tool schemas and logic; deployment-specific entry points (src/index.ts for Smithery, api/mcp.ts for Vercel) adapt the core to different transports without code duplication.","intents":["I want to use Exa search directly within Claude without writing custom API integration code","I need to deploy Exa search as a tool accessible to multiple MCP clients","I want to host Exa search capabilities on a serverless platform with minimal infrastructure"],"best_for":["Teams integrating Exa into Claude or other MCP-compatible AI assistants","Developers building multi-client AI applications requiring standardized tool interfaces","Organizations deploying AI agents on serverless platforms (Vercel, AWS Lambda)"],"limitations":["MCP protocol overhead adds ~50-100ms latency per tool invocation","Stdio transport limited to local deployment; HTTP/SSE requires public endpoint","Tool schema validation happens on both client and server; schema mismatches cause silent failures","No built-in caching or request deduplication across multiple clients"],"requires":["MCP-compatible client (Claude, VS Code with MCP extension, Cursor, etc.)","Node.js 16+ for local deployment or Vercel account for serverless","Exa API key configured as environment variable"],"input_types":["MCP tool invocation requests (JSON-RPC 2.0 format)"],"output_types":["MCP tool response (JSON-RPC 2.0 result or error)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_4","uri":"capability://tool.use.integration.dynamic.tool.registration.with.configuration.schema","name":"dynamic tool registration with configuration schema","description":"Allows runtime configuration of which tools are exposed and how they behave through a configSchema defined in src/index.ts. The initializeMcpServer function in src/mcp-handler.ts reads configuration and conditionally registers tools (web_search_exa, web_fetch_exa, web_search_advanced_exa) with their respective input schemas. This enables deployment-time tool selection without code changes, supporting different use cases (e.g., disabling advanced search for free tier users).","intents":["I want to expose only basic search tools to free tier users and advanced filters to paid users","I need to configure tool availability based on deployment environment (dev vs production)","I want to customize tool parameters (result limits, timeout values) per deployment"],"best_for":["SaaS platforms offering tiered access to Exa capabilities","Multi-tenant deployments requiring per-customer tool configuration","Teams managing multiple Exa MCP server instances with different feature sets"],"limitations":["Configuration changes require server restart; no hot-reload support","Schema validation errors are caught at startup, not runtime","No per-request tool availability override; configuration is global per server instance","Limited to predefined tools; adding new tools requires code changes"],"requires":["Understanding of Smithery configSchema format","Environment variables or config files for tool selection","Ability to restart server for configuration changes"],"input_types":["JSON configuration object (tool names, parameters)"],"output_types":["Registered MCP tool schema with input/output specifications"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_5","uri":"capability://tool.use.integration.type.safe.api.request.response.handling.with.validation","name":"type-safe api request/response handling with validation","description":"Defines strict TypeScript interfaces in src/types.ts for all Exa API requests and responses, ensuring compile-time type safety and runtime validation. The server validates incoming MCP tool parameters against these types before forwarding to Exa API, and validates Exa responses before returning to clients. This prevents type mismatches, malformed requests, and unexpected response structures from propagating to downstream consumers.","intents":["I want to ensure my AI agent never sends malformed requests to Exa API","I need to catch type errors at development time, not in production","I want to validate that Exa API responses match expected schemas before processing"],"best_for":["Production AI applications requiring high reliability","Teams with strict code quality standards and type safety requirements","Systems integrating Exa with multiple downstream consumers (databases, caches, APIs)"],"limitations":["TypeScript-only; no runtime validation for JavaScript clients","Type definitions must be manually updated when Exa API changes","Validation adds ~10-20ms overhead per request","Complex nested types can be difficult to maintain across versions"],"requires":["TypeScript 4.5+ for type checking","Understanding of Exa API request/response structure","Build step to compile TypeScript to JavaScript"],"input_types":["MCP tool parameters (any JSON)"],"output_types":["Validated TypeScript objects matching defined interfaces"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_6","uri":"capability://safety.moderation.error.handling.and.logging.with.structured.output","name":"error handling and logging with structured output","description":"Implements comprehensive error handling across the request lifecycle: validates input parameters, catches Exa API errors, handles network timeouts, and returns structured error responses to MCP clients. The server logs errors with context (request ID, tool name, parameters) to aid debugging. Error responses follow MCP error format, allowing clients to distinguish between invalid input, API failures, and transient errors.","intents":["I need to understand why a search failed (invalid query, API quota exceeded, network error)","I want my AI agent to handle search failures gracefully and retry appropriately","I need detailed logs to debug integration issues in production"],"best_for":["Production deployments requiring observability and debugging","AI agents that need to distinguish between retryable and permanent failures","Teams operating multiple Exa MCP server instances"],"limitations":["Error messages may leak sensitive information (API keys, internal URLs) if not sanitized","Logging to stdout/stderr can be verbose; no built-in log aggregation","Error context is limited to request-level information; no distributed tracing","Timeout handling depends on underlying HTTP client; may vary across transports"],"requires":["Logging infrastructure to capture stdout/stderr","Error handling logic in MCP client to process error responses","Monitoring tools to track error rates and patterns"],"input_types":["MCP tool invocation (any input)"],"output_types":["MCP error response with error code, message, and optional context"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_7","uri":"capability://planning.reasoning.research.orchestration.with.multi.step.search.workflows","name":"research orchestration with multi-step search workflows","description":"Provides a research orchestrator pattern (documented in SKILL.md) that chains multiple search and fetch operations to answer complex research questions. The orchestrator can execute semantic searches, fetch full content from top results, filter by domain/date, and synthesize findings into coherent answers. This enables AI agents to conduct multi-step research without explicit step-by-step prompting, automating common research patterns.","intents":["I want my AI agent to automatically conduct multi-step research (search, fetch, analyze) without explicit instructions","I need to find and synthesize information from multiple sources to answer a complex question","I want to automate research workflows that currently require manual web browsing"],"best_for":["AI agents performing complex research tasks (market analysis, competitive intelligence, academic research)","Automated research pipelines that need to synthesize information from multiple sources","Teams building domain-specific research assistants"],"limitations":["Orchestration logic is defined in prompts/skills, not in code; harder to version control and test","No built-in deduplication; may fetch and analyze duplicate content from different sources","Requires careful prompt engineering to avoid infinite loops or excessive API calls","Results depend on quality of intermediate search results; garbage in, garbage out"],"requires":["Understanding of research orchestration patterns and prompt design","AI client capable of multi-step tool invocation (Claude with extended thinking, etc.)","Sufficient API quota for multi-step workflows"],"input_types":["natural language research question"],"output_types":["synthesized research findings with source citations"],"categories":["planning-reasoning","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_8","uri":"capability://automation.workflow.multi.deployment.target.support.with.transport.abstraction","name":"multi-deployment target support with transport abstraction","description":"Abstracts the transport layer from tool logic, enabling deployment across stdio (local), HTTP/SSE (hosted), and serverless (Vercel) without code duplication. The core tool logic in src/mcp-handler.ts is transport-agnostic; deployment-specific entry points (src/index.ts for Smithery, api/mcp.ts for Vercel) handle transport details. This allows a single codebase to serve local development, cloud-hosted instances, and serverless functions.","intents":["I want to develop locally with stdio transport and deploy to Vercel without code changes","I need to run Exa MCP server in multiple environments (local, Docker, serverless) with the same code","I want to migrate from local to cloud deployment without refactoring"],"best_for":["Teams deploying across multiple environments (dev, staging, production)","Developers wanting local development with easy cloud deployment","Organizations using serverless platforms (Vercel, AWS Lambda, Google Cloud Functions)"],"limitations":["Transport abstraction adds complexity; harder to debug transport-specific issues","Stdio transport limited to local use; HTTP/SSE requires public endpoint and CORS handling","Serverless deployments have cold start latency (~1-2s); not suitable for latency-sensitive applications","Different transports have different timeout and resource limits"],"requires":["Node.js 16+ for local deployment","Docker for containerized deployment","Vercel account for serverless deployment","Understanding of MCP transport mechanisms"],"input_types":["MCP requests (format varies by transport: stdio JSON, HTTP POST, etc.)"],"output_types":["MCP responses (format varies by transport)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__cap_9","uri":"capability://safety.moderation.api.key.management.and.authentication.with.environment.variables","name":"api key management and authentication with environment variables","description":"Manages Exa API authentication through environment variables (EXA_API_KEY), supporting both local development and cloud deployments. The server reads the API key at startup and includes it in all Exa API requests. This approach avoids hardcoding credentials and supports standard deployment patterns (environment variable injection in Docker, Vercel, etc.).","intents":["I want to securely manage Exa API keys across local and cloud deployments","I need to rotate API keys without redeploying code","I want to use different API keys for different environments (dev, staging, production)"],"best_for":["Production deployments requiring secure credential management","Teams using CI/CD pipelines with environment-specific secrets","Multi-tenant deployments with per-customer API keys"],"limitations":["Environment variables visible in process listing; not suitable for highly sensitive credentials","No built-in API key rotation; requires manual environment variable updates","API key leakage in logs or error messages can compromise security","No per-request API key override; single key per server instance"],"requires":["EXA_API_KEY environment variable set before server startup","Secure secret management in deployment platform (Docker secrets, Vercel environment variables, etc.)","Access control to prevent unauthorized API key exposure"],"input_types":["environment variable (string)"],"output_types":["authenticated Exa API requests"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"exa-mcp-server__headline","uri":"capability://search.retrieval.mcp.server.for.ai.powered.web.search","name":"mcp server for ai-powered web search","description":"The Exa MCP Server is an advanced Model Context Protocol server that connects AI assistants to Exa's neural web search capabilities, enabling real-time semantic search and content retrieval with AI-driven relevance ranking.","intents":["best MCP server for AI search","MCP server for real-time web data","AI web search solutions","neural search framework for AI assistants","MCP protocol integration for AI applications"],"best_for":["AI developers","researchers","data scientists"],"limitations":[],"requires":[],"input_types":[],"output_types":[],"categories":["search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":76,"verified":false,"data_access_risk":"high","permissions":["Exa API key (free tier available)","MCP client compatible with stdio or HTTP/SSE transport","Node.js 16+ for local deployment","Exa API key with web_fetch_exa tool enabled","Valid, publicly accessible URL","MCP client with tool invocation support","Exa API key with known quota limits","Timeout configuration (likely in environment variables or config file)","Client-side retry logic to handle rate limit responses","Exa API key (some filters require paid tier)"],"failure_modes":["Requires valid Exa API key with active quota; free tier has rate limits","Results depend on Exa's index freshness; very new content may not be indexed","Cannot search within password-protected or dynamically-rendered content","Semantic ranking may return unexpected results for highly technical or niche queries","Cannot fetch content from pages requiring JavaScript execution or authentication","Respects robots.txt and may fail on sites with strict crawling restrictions","Large pages (>10MB) may be truncated or timeout","Dynamic content loaded after page render is not captured","Timeout handling is transport-specific — stdio, HTTP/SSE, and serverless have different timeout semantics","Rate limit detection is reactive — server detects 429 responses after the request is made, not before","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.62,"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":"2026-06-17T09:51:04.691Z","last_scraped_at":null,"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=exa-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=exa-mcp-server"}},"signature":"vHYIIaz5dLHujqq2NjYM4PNpo+srUeWILWSeQkqE1t4Y1liQ/pE+X/pyDLJuPhg9nBLQUJzL6rHOp2EDfvGMAg==","signedAt":"2026-06-23T14:24:13.876Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/exa-mcp-server","artifact":"https://unfragile.ai/exa-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=exa-mcp-server","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"}}