{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github_mcp-exa-labs-exa-mcp-server","slug":"mcp-exa-labs-exa-mcp-server","name":"exa-mcp-server","type":"mcp","url":"https://github.com/exa-labs/exa-mcp-server","page_url":"https://unfragile.ai/mcp-exa-labs-exa-mcp-server","categories":["mcp-servers"],"tags":["code-search","codesearch","crawling","mcp","mcp-server","model-context-protocol","web-search","websearch"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github_mcp-exa-labs-exa-mcp-server__cap_0","uri":"capability://search.retrieval.semantic.web.search.via.mcp.protocol","name":"semantic web search via mcp protocol","description":"Executes semantic web searches through the Model Context Protocol by translating natural language queries into Exa API requests, returning ranked results with relevance scoring. The server implements the MCP tool registry pattern where web_search_exa is registered as a callable tool with standardized input/output schemas, allowing Claude, VS Code, Cursor, and other MCP-compatible clients to invoke searches without direct API knowledge. Results include title, URL, snippet, and relevance metadata optimized for LLM context windows.","intents":["I need to search the web for current information to answer a user's question","I want to find relevant sources and URLs related to a specific topic","I need to retrieve web search results within an AI agent workflow without managing API calls directly"],"best_for":["AI agents and assistants built on Claude, VS Code, or Cursor that need real-time web access","developers building LLM-powered research tools who want standardized MCP integration","teams migrating from REST API calls to the Model Context Protocol for tool orchestration"],"limitations":["Requires valid Exa API key with active quota; rate limits depend on Exa subscription tier","Search results are limited to Exa's indexed web corpus; cannot search private/paywalled content","Semantic search quality depends on query clarity; ambiguous queries may return less relevant results","MCP transport adds ~50-200ms latency per request depending on deployment (stdio vs HTTP/SSE)"],"requires":["Exa API key (obtainable from exa.ai)","MCP-compatible client (Claude Desktop, VS Code with MCP extension, Cursor, or custom MCP client)","Node.js 18+ for local deployment or HTTP endpoint access for serverless deployments"],"input_types":["text query string (natural language or structured search syntax)"],"output_types":["structured JSON with array of search results containing title, url, snippet, publishedDate, score"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_1","uri":"capability://data.processing.analysis.web.content.fetching.and.cleaning","name":"web content fetching and cleaning","description":"Retrieves full HTML content from specified URLs and returns cleaned, structured text optimized for LLM consumption. The web_fetch_exa tool uses Exa's content extraction pipeline to strip boilerplate (navigation, ads, scripts), extract main content, and format it as readable text with preserved structure. This replaces the deprecated crawling_exa tool and integrates with the MCP tool registry to allow AI clients to fetch and analyze specific web pages without managing HTML parsing or cleaning logic.","intents":["I need to retrieve the full text content of a specific URL for analysis or citation","I want to extract the main article content from a webpage without boilerplate or ads","I need to fetch and process multiple URLs within an agent workflow to gather detailed information"],"best_for":["AI agents that need to read full articles or documentation pages for detailed analysis","research assistants that must cite specific sources with full content context","developers building content aggregation or knowledge extraction pipelines"],"limitations":["Content extraction quality varies by page structure; complex layouts or JavaScript-rendered content may be incomplete","Large pages (>10MB) may be truncated to fit LLM context windows","Does not execute JavaScript; dynamic content loaded client-side will not be captured","Some sites with aggressive anti-scraping measures may return partial or blocked content"],"requires":["Exa API key with web fetch capability enabled","Valid, publicly accessible URL (no authentication required for target page)","MCP-compatible client to invoke the tool"],"input_types":["text URL string"],"output_types":["structured JSON containing cleaned text content, title, author, publish date, and metadata"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_10","uri":"capability://safety.moderation.exa.api.authentication.and.credential.management","name":"exa api authentication and credential management","description":"Manages Exa API authentication by accepting an API key through environment variables (EXA_API_KEY) and including it in all requests to the Exa API. The server validates that the API key is present at startup and includes it in request headers or query parameters as required by the Exa API. Credentials are never logged or exposed in error messages, protecting sensitive data. The authentication mechanism is transparent to MCP clients, which do not need to provide credentials directly.","intents":["I need to authenticate with Exa API without exposing credentials to clients","I want to ensure the API key is valid before the server starts accepting requests","I need to rotate API keys without redeploying the server"],"best_for":["teams deploying MCP servers that need to manage Exa API credentials securely","organizations with strict credential management policies","developers building production MCP servers"],"limitations":["API key must be set as environment variable; no support for credential files or secret managers","API key is loaded at server startup; rotation requires server restart","No built-in rate limiting or quota management; relies on Exa API rate limits"],"requires":["Valid Exa API key (obtainable from exa.ai)","Environment variable EXA_API_KEY set before server startup"],"input_types":["environment variable with API key string"],"output_types":["authenticated requests to Exa API with credentials included"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_11","uri":"capability://planning.reasoning.research.orchestration.and.agent.skill.composition","name":"research orchestration and agent skill composition","description":"Provides a research orchestration framework (documented in SKILL.md) that enables AI agents to compose multiple search and fetch operations into complex research workflows. The framework allows agents to chain searches (e.g., search for topic, fetch top results, search for related topics) and coordinate results across multiple tool calls. This is implemented through the standard MCP tool interface, allowing agents to call tools sequentially and use results from one call as input to the next. The framework is agent-agnostic, working with any MCP-compatible agent that supports tool calling.","intents":["I want to build an AI agent that performs multi-step research (search, fetch, analyze, search again)","I need to coordinate results from multiple web searches into a cohesive research output","I want to enable agents to autonomously research topics by chaining tool calls"],"best_for":["AI agents and assistants that need to perform complex research workflows","developers building autonomous research tools","teams building AI-powered content creation or analysis systems"],"limitations":["Research orchestration is agent-dependent; the server provides tools but agents must implement orchestration logic","No built-in result deduplication or conflict resolution across multiple searches","Agent reasoning quality depends on the underlying LLM; complex research may require explicit prompting"],"requires":["MCP-compatible agent with tool calling support","Exa API key with sufficient quota for multiple requests"],"input_types":["agent prompts requesting research on a topic"],"output_types":["structured research results from chained tool calls"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_12","uri":"capability://automation.workflow.docker.and.containerized.deployment","name":"docker and containerized deployment","description":"Supports Docker-based deployment through a Dockerfile that packages the MCP server with all dependencies, enabling consistent deployment across environments. The Docker image includes Node.js runtime, server code, and dependencies, and can be deployed to any Docker-compatible platform (Kubernetes, Docker Compose, cloud container services). The image exposes the MCP server via HTTP/SSE transport, making it accessible to remote clients. Environment variables (including EXA_API_KEY) are passed at container runtime, enabling credential management without rebuilding images.","intents":["I want to deploy the MCP server in a Kubernetes cluster","I need to run the server in a Docker container for consistency across dev/prod","I want to scale the MCP server horizontally using container orchestration"],"best_for":["teams using Kubernetes or Docker Compose for infrastructure","organizations with containerized deployment pipelines","developers building cloud-native MCP server deployments"],"limitations":["Docker deployment adds container overhead (~50-100MB image size)","Horizontal scaling requires external load balancing; server itself is stateless","Container startup time adds ~1-2 seconds to deployment"],"requires":["Docker runtime (Docker Desktop, Docker Engine, or compatible)","Dockerfile in repository","Environment variables passed at container runtime"],"input_types":["Docker build/run commands with environment variables"],"output_types":["running Docker container exposing MCP server via HTTP/SSE"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_13","uri":"capability://automation.workflow.vercel.serverless.deployment.with.http.sse.transport","name":"vercel serverless deployment with http/sse transport","description":"Enables serverless deployment on Vercel through an HTTP/SSE transport adapter (api/mcp.ts) that translates HTTP requests into MCP protocol messages. The adapter handles incoming HTTP requests, parses them as MCP tool calls, executes the tools, and returns results as HTTP responses. This allows the MCP server to run as a Vercel serverless function, scaling automatically based on demand without managing infrastructure. The same core tool logic (src/mcp-handler.ts) is reused across stdio and serverless deployments.","intents":["I want to deploy the MCP server on Vercel without managing servers","I need the server to scale automatically based on traffic","I want to integrate the MCP server into a Vercel-based application"],"best_for":["teams using Vercel for application hosting","developers building serverless MCP integrations","organizations that want zero-infrastructure MCP deployment"],"limitations":["Serverless functions have cold start latency (~1-3 seconds on first invocation)","Execution timeout limits (typically 10-60 seconds) may affect long-running searches","Vercel free tier has limited invocation quota; production use requires paid plan","No persistent state across invocations; each request is stateless"],"requires":["Vercel account and CLI","Vercel project with Node.js runtime","Environment variables configured in Vercel dashboard"],"input_types":["HTTP POST requests with MCP tool call payload"],"output_types":["HTTP responses with MCP tool result payload"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_2","uri":"capability://search.retrieval.advanced.web.search.with.granular.filtering","name":"advanced web search with granular filtering","description":"Executes semantic web searches with fine-grained control over result filtering through the web_search_advanced_exa tool, supporting domain whitelisting/blacklisting, date range filtering, content category filtering, and result ranking customization. The tool accepts structured filter parameters that are translated into Exa API query constraints, enabling researchers and agents to narrow search scope to specific sources, time periods, or content types. Results are returned with full metadata including publication date, domain, and category tags.","intents":["I need to search only academic or news sources, excluding blogs and social media","I want to find recent information published within the last 30 days on a specific topic","I need to search within a whitelist of trusted domains or exclude known unreliable sources"],"best_for":["researchers and analysts who need precise source control and temporal filtering","compliance and risk teams that must restrict searches to approved domains","AI agents building specialized research workflows with domain-specific constraints"],"limitations":["Advanced filtering reduces result set size; overly restrictive filters may return zero results","Domain filtering is based on Exa's domain classification; edge cases or new domains may not be categorized","Category filtering relies on Exa's content classification; misclassified pages may be included or excluded incorrectly","Date filtering applies to Exa's indexed publication date, which may differ from actual content creation date"],"requires":["Exa API key with advanced search features enabled","Understanding of filter syntax and available categories/domains","MCP-compatible client"],"input_types":["text query string","optional filter object with properties: includeDomains (array), excludeDomains (array), startPublishedDate (ISO 8601), endPublishedDate (ISO 8601), category (string)"],"output_types":["structured JSON with filtered search results including domain, publishedDate, category, and relevance score"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_3","uri":"capability://tool.use.integration.mcp.tool.registry.and.dynamic.tool.registration","name":"mcp tool registry and dynamic tool registration","description":"Implements the Model Context Protocol's tool registry pattern through the initializeMcpServer function in src/mcp-handler.ts, which dynamically registers web_search_exa, web_fetch_exa, and web_search_advanced_exa as callable tools with standardized JSON schemas. Each tool is registered with input parameter definitions, descriptions, and execution handlers that translate MCP tool calls into Exa API requests. The registry supports configuration-driven tool selection, allowing deployments to enable/disable tools based on environment variables or deployment context.","intents":["I need to expose Exa search capabilities as discoverable tools to MCP-compatible clients","I want to configure which tools are available in different deployment environments","I need to standardize tool invocation across multiple AI clients (Claude, VS Code, Cursor) with a single server"],"best_for":["developers deploying MCP servers that need to integrate Exa search capabilities","teams managing multiple MCP client integrations who need a single canonical tool registry","organizations building custom MCP servers that want to extend Exa tools with additional logic"],"limitations":["Tool registration is static at server startup; adding/removing tools requires server restart","MCP schema validation is performed by the client; invalid tool calls will fail at client level","Tool discovery is read-only; clients cannot dynamically register new tools at runtime"],"requires":["Node.js 18+ runtime","MCP server framework (provided by @modelcontextprotocol/sdk)","Exa API key for tool execution"],"input_types":["MCP tool call with tool name and parameters object"],"output_types":["MCP tool result with success/error status and structured data payload"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_4","uri":"capability://automation.workflow.multi.transport.deployment.orchestration","name":"multi-transport deployment orchestration","description":"Supports deployment across multiple transport mechanisms (stdio for local development, HTTP/SSE for hosted endpoints, serverless for Vercel) from a single codebase through modular architecture. The entry point src/index.ts handles Smithery-based deployments with stdio transport, while api/mcp.ts provides HTTP/SSE transport for serverless environments. The core MCP handler logic in src/mcp-handler.ts is transport-agnostic, allowing the same tool implementations to work across deployment targets. Configuration is managed through environment variables and deployment-specific entry points.","intents":["I want to deploy the MCP server locally for development with stdio transport","I need to host the MCP server as an HTTP endpoint for remote clients","I want to deploy the server serverless on Vercel without managing infrastructure"],"best_for":["developers building MCP servers who need flexibility across local, hosted, and serverless deployments","teams managing multiple deployment environments (dev, staging, production)","organizations using Vercel or similar serverless platforms who want MCP integration"],"limitations":["Stdio transport is limited to local or SSH-based connections; not suitable for remote clients","HTTP/SSE transport adds network latency compared to stdio; typical latency 50-200ms per request","Serverless deployments have cold start overhead (~1-3 seconds on first invocation)","State is not persisted across serverless invocations; each request is stateless"],"requires":["Node.js 18+ for local deployment","Vercel account and CLI for serverless deployment","Docker for containerized deployment","Environment variables: EXA_API_KEY, optional deployment-specific config"],"input_types":["deployment configuration (environment variables, entry point selection)"],"output_types":["running MCP server accessible via stdio, HTTP/SSE, or serverless endpoint"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_5","uri":"capability://code.generation.editing.type.safe.api.request.response.handling","name":"type-safe api request/response handling","description":"Implements strict TypeScript type definitions in src/types.ts for all Exa API requests and responses, ensuring compile-time type safety and runtime validation. The type system defines contracts for search queries, fetch requests, filter parameters, and result objects, preventing type mismatches between MCP tool invocations and Exa API calls. Type definitions are used for both client-side validation (before sending to Exa) and server-side response parsing, reducing runtime errors and improving IDE autocomplete for developers extending the server.","intents":["I want to ensure type safety when calling Exa API from the MCP server","I need to validate MCP tool parameters before forwarding to Exa API","I want IDE autocomplete and type hints when extending the server with new tools"],"best_for":["TypeScript developers building or extending the MCP server","teams that prioritize type safety and compile-time error detection","developers integrating Exa API calls into larger TypeScript projects"],"limitations":["Type definitions are TypeScript-only; Python or other language clients must implement their own types","Runtime validation requires explicit type guards; TypeScript types are erased at runtime","Type definitions must be manually updated when Exa API changes; no automatic schema synchronization"],"requires":["TypeScript 4.5+ compiler","Knowledge of TypeScript type system and generics"],"input_types":["TypeScript source code with type annotations"],"output_types":["compiled JavaScript with type information available in .d.ts files"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_6","uri":"capability://automation.workflow.error.handling.and.logging.infrastructure","name":"error handling and logging infrastructure","description":"Implements structured error handling and logging throughout the server to capture API failures, validation errors, and request/response issues. The error handling strategy includes try-catch blocks around Exa API calls, validation of MCP tool parameters, and structured logging of request/response data for debugging. Errors are propagated to MCP clients with descriptive messages, enabling clients to handle failures gracefully. Logging infrastructure supports different verbosity levels and can be configured via environment variables for development vs. production deployments.","intents":["I need to debug why a web search or fetch request failed","I want to monitor server health and track API errors in production","I need to understand request/response flow for troubleshooting client integration issues"],"best_for":["developers debugging MCP server issues during development","operations teams monitoring production deployments","teams integrating the MCP server with custom clients who need detailed error information"],"limitations":["Logging verbosity must be configured at server startup; cannot be changed dynamically","Sensitive data (API keys, full request bodies) should be excluded from logs; requires careful filtering","Log aggregation requires external tools (e.g., CloudWatch, Datadog); server does not provide built-in aggregation"],"requires":["Node.js logging library (built-in or third-party like winston, pino)","Environment variable configuration for log level"],"input_types":["error objects, request/response data"],"output_types":["structured log entries with timestamp, level, message, and context"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_7","uri":"capability://automation.workflow.configuration.driven.tool.selection.and.customization","name":"configuration-driven tool selection and customization","description":"Allows deployment-time configuration of which tools are enabled and how they behave through environment variables and configuration schemas. The configSchema in src/index.ts defines available configuration options, and the initializeMcpServer function uses these settings to selectively register tools and customize their behavior. This enables different deployments (e.g., research-focused vs. general-purpose) to expose different tool sets without code changes. Configuration is validated at server startup, ensuring invalid configurations are caught early.","intents":["I want to enable only web_search_exa in production and all tools in development","I need to customize search result limits or timeout values per deployment","I want to restrict certain tools to specific user groups or use cases"],"best_for":["teams managing multiple MCP server deployments with different tool sets","organizations that need environment-specific configuration without code changes","developers building customizable MCP servers for different use cases"],"limitations":["Configuration changes require server restart; no hot-reload support","Configuration validation is basic; complex conditional logic requires code changes","Environment variables are the only configuration mechanism; no config file support"],"requires":["Understanding of available configuration options","Ability to set environment variables in deployment environment"],"input_types":["environment variables with configuration key-value pairs"],"output_types":["server initialized with selected tools and customized behavior"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_8","uri":"capability://tool.use.integration.mcp.client.compatibility.and.discovery","name":"mcp client compatibility and discovery","description":"Implements the Model Context Protocol specification to ensure compatibility with MCP-capable clients including Claude Desktop, VS Code with MCP extension, Cursor, and custom MCP clients. The server exposes tools through the MCP tool discovery mechanism, allowing clients to query available tools and their schemas at connection time. Tool schemas include parameter definitions, descriptions, and examples, enabling clients to provide autocomplete and validation. The server handles MCP protocol messages (tool calls, results, errors) according to the specification.","intents":["I want to use Exa search in Claude Desktop without custom integration code","I need to make Exa tools available in VS Code for code-aware research","I want to build a custom MCP client that can discover and call Exa tools"],"best_for":["users of Claude Desktop, VS Code, Cursor who want Exa integration","developers building custom MCP clients that need Exa search capabilities","teams deploying MCP servers that need broad client compatibility"],"limitations":["MCP client support varies; older clients may not support all MCP features","Tool discovery is read-only; clients cannot modify tool definitions at runtime","Some clients have limitations on tool parameter complexity; deeply nested schemas may not work"],"requires":["MCP-compatible client (Claude Desktop, VS Code 1.80+, Cursor, or custom implementation)","MCP server running and accessible to the client"],"input_types":["MCP protocol messages (tool calls with parameters)"],"output_types":["MCP protocol messages (tool results, errors, tool definitions for discovery)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-exa-labs-exa-mcp-server__cap_9","uri":"capability://automation.workflow.request.lifecycle.and.data.flow.orchestration","name":"request lifecycle and data flow orchestration","description":"Manages the complete request lifecycle from MCP tool invocation through Exa API call to result formatting and return to the client. The data flow begins with the client sending an MCP tool call message, which the server parses and validates against the tool schema. The server then constructs an Exa API request with the validated parameters, handles authentication, sends the request, parses the response, formats results for the MCP client, and returns the result message. Error handling is integrated throughout the lifecycle, with failures at any stage being caught and returned as MCP error messages.","intents":["I need to understand how a tool call flows from client to Exa API and back","I want to debug a specific request that failed partway through the pipeline","I need to optimize request/response handling for latency"],"best_for":["developers debugging MCP server issues","teams optimizing server performance and latency","developers extending the server with new tools who need to understand the request flow"],"limitations":["Request lifecycle is synchronous; no support for async streaming responses","Large responses may be truncated to fit MCP message size limits","Error handling is best-effort; some edge cases may not be caught"],"requires":["Understanding of MCP protocol message format","Knowledge of Exa API request/response format"],"input_types":["MCP tool call message with tool name and parameters"],"output_types":["MCP tool result message with success/error status and data payload"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":47,"verified":false,"data_access_risk":"high","permissions":["Exa API key (obtainable from exa.ai)","MCP-compatible client (Claude Desktop, VS Code with MCP extension, Cursor, or custom MCP client)","Node.js 18+ for local deployment or HTTP endpoint access for serverless deployments","Exa API key with web fetch capability enabled","Valid, publicly accessible URL (no authentication required for target page)","MCP-compatible client to invoke the tool","Valid Exa API key (obtainable from exa.ai)","Environment variable EXA_API_KEY set before server startup","MCP-compatible agent with tool calling support","Exa API key with sufficient quota for multiple requests"],"failure_modes":["Requires valid Exa API key with active quota; rate limits depend on Exa subscription tier","Search results are limited to Exa's indexed web corpus; cannot search private/paywalled content","Semantic search quality depends on query clarity; ambiguous queries may return less relevant results","MCP transport adds ~50-200ms latency per request depending on deployment (stdio vs HTTP/SSE)","Content extraction quality varies by page structure; complex layouts or JavaScript-rendered content may be incomplete","Large pages (>10MB) may be truncated to fit LLM context windows","Does not execute JavaScript; dynamic content loaded client-side will not be captured","Some sites with aggressive anti-scraping measures may return partial or blocked content","API key must be set as environment variable; no support for credential files or secret managers","API key is loaded at server startup; rotation requires server restart","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.5659273810277619,"quality":0.35,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"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":"2026-05-24T12:16:22.065Z","last_scraped_at":"2026-05-03T14:23:31.492Z","last_commit":"2026-05-01T19:53:39Z"},"community":{"stars":4371,"forks":327,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-exa-labs-exa-mcp-server","compare_url":"https://unfragile.ai/compare?artifact=mcp-exa-labs-exa-mcp-server"}},"signature":"jWLMgxqLgDW8iIEXfmkHdffBhnRLAjDUjeScbQtw81YO1yrSO659tW9pK9JTV35rMgfUNEmCM2qHuEe7+qLHAg==","signedAt":"2026-06-22T09:44:23.515Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-exa-labs-exa-mcp-server","artifact":"https://unfragile.ai/mcp-exa-labs-exa-mcp-server","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-exa-labs-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"}}