{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_abdalla-emad-eldin-outworx-docs","slug":"abdalla-emad-eldin-outworx-docs","name":"Outworx-docs","type":"mcp","url":"https://smithery.ai/servers/abdalla-emad-eldin/Outworx-docs","page_url":"https://unfragile.ai/abdalla-emad-eldin-outworx-docs","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:abdalla-emad-eldin/Outworx-docs"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_abdalla-emad-eldin-outworx-docs__cap_0","uri":"capability://tool.use.integration.mcp.compliant.documentation.server.with.claude.integration","name":"mcp-compliant documentation server with claude integration","description":"Exposes documentation content through the Model Context Protocol (MCP) interface, allowing Claude and other MCP-compatible clients to query and retrieve documentation programmatically. Implements MCP's resource and tool abstractions to make docs queryable as structured data rather than static files, enabling LLM-aware context injection into conversations and agent workflows.","intents":["I want Claude to have access to my product documentation without copy-pasting content into every conversation","I need to build an AI agent that can answer customer questions by referencing live documentation","I want to enable semantic search over documentation through an LLM interface"],"best_for":["Product teams building AI-powered customer support agents","Documentation teams integrating docs into LLM workflows","Developers building Claude-based tools that need contextual documentation access"],"limitations":["Limited to MCP-compatible clients (Claude, some open-source tools) — no REST API fallback","Documentation must be pre-indexed or discoverable via MCP resource listing — no full-text search backend assumed","No built-in authentication or access control — relies on MCP server deployment security"],"requires":["MCP client implementation (Claude desktop, Claude API with MCP support, or compatible tool)","Documentation source in a format the server can parse (likely Markdown, HTML, or structured text)","Network connectivity between MCP client and server"],"input_types":["documentation queries (natural language or structured)","resource identifiers (doc paths, section names)"],"output_types":["documentation text/content","structured metadata about docs","search results or filtered doc sections"],"categories":["tool-use-integration","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_abdalla-emad-eldin-outworx-docs__cap_1","uri":"capability://search.retrieval.documentation.resource.enumeration.and.discovery","name":"documentation resource enumeration and discovery","description":"Provides MCP resource listing capabilities that allow clients to discover available documentation sections, hierarchies, and metadata without prior knowledge of doc structure. Implements MCP's resource discovery pattern to expose documentation as queryable resources with URIs, enabling clients to browse and select relevant docs before requesting content.","intents":["I want Claude to know what documentation sections exist before I ask a question","I need to build a doc browser UI that lists all available documentation","I want agents to autonomously discover which docs are relevant to a query"],"best_for":["Teams with large documentation sets needing intelligent navigation","AI agents that need to discover relevant docs before retrieval","Documentation platforms integrating MCP for discoverability"],"limitations":["Resource listing may be expensive for very large documentation sets (1000+ pages) — no pagination mentioned","No filtering or search at discovery layer — returns full resource list","Hierarchy representation depends on MCP resource URI conventions — no custom taxonomy support assumed"],"requires":["MCP client with resource listing support","Documentation organized in a discoverable structure (file hierarchy, database, etc.)"],"input_types":["resource discovery requests (MCP list_resources calls)"],"output_types":["resource metadata (URIs, names, descriptions)","hierarchical documentation structure"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_abdalla-emad-eldin-outworx-docs__cap_2","uri":"capability://memory.knowledge.documentation.content.retrieval.via.mcp.resource.reads","name":"documentation content retrieval via mcp resource reads","description":"Implements MCP's resource read operation to fetch full documentation content by resource URI, returning formatted text or structured data. Handles content parsing, formatting, and optional truncation for large documents, allowing clients to retrieve specific doc sections on-demand without loading entire documentation sets into context.","intents":["I want to fetch a specific documentation page when Claude asks for it","I need to retrieve documentation content efficiently without pre-loading everything","I want to get documentation in a format optimized for LLM consumption (plain text, markdown, etc.)"],"best_for":["LLM agents that need on-demand documentation retrieval","Chat interfaces augmenting conversations with live documentation","Documentation systems with large content sets requiring lazy loading"],"limitations":["No streaming for large documents — entire content must fit in response","Content formatting may lose semantic structure (tables, code blocks) depending on output format","No caching layer mentioned — repeated requests re-fetch from source"],"requires":["MCP client with resource read support","Valid resource URI for the documentation to retrieve","Documentation source accessible to the MCP server"],"input_types":["resource URIs (documentation paths)","optional format hints (markdown, plain text, etc.)"],"output_types":["documentation text content","formatted markdown or HTML","structured content with metadata"],"categories":["memory-knowledge","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_abdalla-emad-eldin-outworx-docs__cap_3","uri":"capability://search.retrieval.tool.based.documentation.search.and.querying","name":"tool-based documentation search and querying","description":"Exposes documentation search and query capabilities as MCP tools, allowing clients to invoke semantic or keyword-based searches over documentation content. Implements MCP's tool calling pattern to provide search as a callable function with parameters like query string, filters, and result limits, enabling agents to autonomously search docs as part of reasoning workflows.","intents":["I want Claude to search documentation for relevant content when answering a question","I need agents to find specific information in docs without knowing exact section names","I want to enable semantic search over documentation through natural language queries"],"best_for":["AI agents needing autonomous documentation search capabilities","Customer support bots that must find relevant docs for user questions","LLM-powered documentation assistants"],"limitations":["Search quality depends on underlying indexing strategy — no details on semantic vs. keyword search","No ranking or relevance scoring mentioned — results may be unordered","Search tool invocation adds latency to agent reasoning loops"],"requires":["MCP client with tool calling support","Documentation indexed or searchable (full-text index, embeddings, or simple grep)","Search parameters defined (query format, filters, result limits)"],"input_types":["search query strings","optional filters (doc section, category, etc.)","result limit parameters"],"output_types":["search results (matching doc sections or pages)","result metadata (relevance score, source URI, excerpt)"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_abdalla-emad-eldin-outworx-docs__cap_4","uri":"capability://memory.knowledge.documentation.metadata.and.schema.exposure","name":"documentation metadata and schema exposure","description":"Provides structured metadata about documentation (titles, descriptions, tags, categories, update timestamps) through MCP resource metadata or tool responses. Enables clients to understand documentation structure, relationships, and freshness without parsing content, supporting intelligent doc selection and prioritization in agent workflows.","intents":["I want Claude to know which documentation is most recent or relevant to a topic","I need agents to prioritize documentation by category or tag when multiple docs match","I want to expose documentation relationships (related docs, dependencies) to LLMs"],"best_for":["Documentation systems with rich metadata (tags, categories, versioning)","Agents that need to rank or filter docs before retrieval","Teams managing documentation relationships and dependencies"],"limitations":["Metadata richness depends on documentation source — may be sparse or missing","No standardized metadata schema — format varies by implementation","Metadata updates may lag behind content changes if not synchronized"],"requires":["Documentation source with structured metadata (frontmatter, database fields, etc.)","MCP server configured to extract and expose metadata"],"input_types":["metadata queries (by tag, category, date range, etc.)"],"output_types":["structured metadata objects (JSON with title, description, tags, timestamps)","filtered doc lists by metadata criteria"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_abdalla-emad-eldin-outworx-docs__cap_5","uri":"capability://memory.knowledge.documentation.metadata.and.annotation.serving","name":"documentation metadata and annotation serving","description":"Exposes rich metadata about documentation resources (author, creation date, last modified, tags, category, difficulty level, related topics) through MCP resource metadata fields. Allows clients to filter, sort, and prioritize documentation based on metadata without reading full content, enabling intelligent documentation selection and context ranking in LLM applications.","intents":["I want Claude to prioritize beginner-friendly documentation when helping new users","I need to filter documentation by category or tags to find relevant sections quickly","I want to know which documentation is most recently updated to ensure accuracy"],"best_for":["documentation systems with rich metadata that enables intelligent filtering","LLM applications that need to rank documentation by relevance or difficulty","teams building documentation recommendation systems"],"limitations":["Metadata quality depends on consistent tagging and annotation practices","No built-in metadata validation — inconsistent or missing metadata reduces effectiveness","Metadata overhead increases MCP response size for resource listings"],"requires":["documentation with structured metadata (frontmatter, database fields, or JSON annotations)","MCP server implementation exposing metadata in resource responses","consistent metadata schema across all documentation"],"input_types":["MCP resource listing requests with metadata filters","metadata queries (e.g., 'all beginner-level docs in category X')"],"output_types":["resource metadata (author, date, tags, category, difficulty, related topics)","filtered or ranked resource lists based on metadata criteria"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":24,"verified":false,"data_access_risk":"high","permissions":["MCP client implementation (Claude desktop, Claude API with MCP support, or compatible tool)","Documentation source in a format the server can parse (likely Markdown, HTML, or structured text)","Network connectivity between MCP client and server","MCP client with resource listing support","Documentation organized in a discoverable structure (file hierarchy, database, etc.)","MCP client with resource read support","Valid resource URI for the documentation to retrieve","Documentation source accessible to the MCP server","MCP client with tool calling support","Documentation indexed or searchable (full-text index, embeddings, or simple grep)"],"failure_modes":["Limited to MCP-compatible clients (Claude, some open-source tools) — no REST API fallback","Documentation must be pre-indexed or discoverable via MCP resource listing — no full-text search backend assumed","No built-in authentication or access control — relies on MCP server deployment security","Resource listing may be expensive for very large documentation sets (1000+ pages) — no pagination mentioned","No filtering or search at discovery layer — returns full resource list","Hierarchy representation depends on MCP resource URI conventions — no custom taxonomy support assumed","No streaming for large documents — entire content must fit in response","Content formatting may lose semantic structure (tables, code blocks) depending on output format","No caching layer mentioned — repeated requests re-fetch from source","Search quality depends on underlying indexing strategy — no details on semantic vs. keyword search","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.22,"ecosystem":0.38999999999999996,"match_graph":0.25,"freshness":0.5,"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":"2026-05-24T12:16:25.061Z","last_scraped_at":"2026-05-03T15:19:22.209Z","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=abdalla-emad-eldin-outworx-docs","compare_url":"https://unfragile.ai/compare?artifact=abdalla-emad-eldin-outworx-docs"}},"signature":"V4PW6txrBsfT+AflOnFIQ0hzRw0kQG8cXPtUz5VocbukDtI3mPDy9HfC7Dq/k4A4g2yrAwv1QsCuFC0FvdbKAA==","signedAt":"2026-06-20T22:43:53.346Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/abdalla-emad-eldin-outworx-docs","artifact":"https://unfragile.ai/abdalla-emad-eldin-outworx-docs","verify":"https://unfragile.ai/api/v1/verify?slug=abdalla-emad-eldin-outworx-docs","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"}}