{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-equally-ai-mcp","slug":"npm-equally-ai-mcp","name":"equally-ai-mcp","type":"mcp","url":"https://www.npmjs.com/package/equally-ai-mcp","page_url":"https://unfragile.ai/npm-equally-ai-mcp","categories":["mcp-servers"],"tags":["accessibility","wcag","compliance","mcp","a11y","audit"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-equally-ai-mcp__cap_0","uri":"capability://tool.use.integration.wcag.accessibility.audit.via.mcp.protocol","name":"wcag accessibility audit via mcp protocol","description":"Exposes accessibility compliance scanning as an MCP tool that integrates with Claude and other LLM clients, enabling real-time WCAG 2.1 violation detection across web content. The tool operates as a stateless MCP server that accepts URLs or HTML content and returns structured accessibility findings mapped to WCAG success criteria levels (A, AA, AAA), allowing LLM agents to reason about and remediate accessibility issues programmatically.","intents":["I want to audit a website for WCAG compliance without leaving my AI chat interface","I need to integrate accessibility scanning into an LLM-powered agent workflow","I want Claude to identify and suggest fixes for accessibility violations in real-time","I need to generate accessibility audit reports programmatically from within an MCP client"],"best_for":["developers building LLM agents that need accessibility compliance verification","accessibility teams using Claude or other MCP-compatible LLMs for audit workflows","teams automating WCAG compliance checks in CI/CD pipelines via LLM orchestration"],"limitations":["MCP protocol overhead adds latency compared to direct API calls — each audit request requires MCP serialization/deserialization","Audit scope limited to static HTML analysis — cannot detect dynamic JavaScript-rendered accessibility issues without headless browser integration","No built-in caching of audit results — repeated scans of identical URLs incur full re-analysis cost","Requires MCP-compatible client (Claude, Cline, etc.) — cannot be used as standalone REST API"],"requires":["Node.js 16+ for MCP server runtime","MCP client implementation (Claude Desktop, Cline, or custom MCP host)","Valid URL or raw HTML content as input","Network access to target URLs if scanning external sites"],"input_types":["URL (string)","HTML content (string)","optional: WCAG conformance level filter (A, AA, AAA)"],"output_types":["structured JSON with violation list","WCAG success criteria mappings","severity levels (critical, major, minor)","remediation suggestions (text)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-equally-ai-mcp__cap_1","uri":"capability://tool.use.integration.mcp.tool.registration.and.schema.definition.for.accessibility.scanning","name":"mcp tool registration and schema definition for accessibility scanning","description":"Implements the MCP tool protocol to register accessibility audit capabilities with a standardized JSON schema, enabling LLM clients to discover, understand, and invoke the tool with proper parameter validation. The tool schema defines input parameters (URL, HTML content, conformance level), output structure (violations array with WCAG mappings), and error handling contracts, allowing MCP hosts to enforce type safety and provide IDE-like autocomplete for accessibility audits.","intents":["I want my MCP client to auto-discover and display available accessibility audit parameters","I need type-safe tool invocation with validation before sending requests to the audit service","I want Claude to understand what accessibility audit parameters are required and optional","I need to expose accessibility scanning as a discoverable capability in an MCP ecosystem"],"best_for":["MCP client developers integrating equally-ai-mcp into their platforms","teams building custom LLM agents that need accessibility tooling with schema validation","organizations standardizing on MCP for tool orchestration across multiple LLM providers"],"limitations":["Schema is static — cannot dynamically adjust parameters based on runtime capabilities or feature flags","No versioning mechanism for tool schema — breaking changes require client-side updates","Schema validation occurs only at MCP protocol level — business logic validation (e.g., valid WCAG levels) must be implemented server-side"],"requires":["MCP protocol implementation (typically Node.js with @modelcontextprotocol/sdk)","JSON schema validation library (built into most MCP implementations)","MCP client that supports tool discovery (Claude, Cline, custom hosts)"],"input_types":["JSON schema definition (internal)","tool invocation parameters from MCP client"],"output_types":["MCP tool schema (JSON)","tool invocation results (JSON)","error responses with MCP error codes"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-equally-ai-mcp__cap_2","uri":"capability://data.processing.analysis.structured.wcag.violation.reporting.with.remediation.guidance","name":"structured wcag violation reporting with remediation guidance","description":"Transforms raw accessibility scan results into structured JSON reports that map violations to specific WCAG 2.1 success criteria (e.g., 1.4.3 Contrast Minimum), include severity classifications, and provide actionable remediation suggestions. The reporting system organizes findings by impact level and includes references to WCAG guidelines, enabling LLM agents to reason about compliance gaps and generate fix recommendations with proper context.","intents":["I want accessibility violations categorized by WCAG success criteria so I can prioritize fixes","I need remediation suggestions for each violation to guide code changes","I want to understand the impact and severity of each accessibility issue","I need to generate compliance reports that map violations to WCAG standards"],"best_for":["accessibility teams needing structured audit data for compliance documentation","LLM agents that need to reason about and prioritize accessibility fixes","developers building automated accessibility remediation workflows"],"limitations":["Remediation suggestions are template-based — may not account for complex design patterns or custom components","Severity classification is rule-based — does not incorporate user impact assessment or real-world accessibility testing","WCAG mapping is limited to 2.1 standard — does not include emerging standards like WCAG 3.0 or EN 301 549","No context about existing fixes — cannot detect if violations have already been addressed in code"],"requires":["accessibility scanning engine (integrated with equally-ai-mcp)","WCAG 2.1 criteria database (internal to the tool)","remediation suggestion templates (built-in or configurable)"],"input_types":["raw accessibility scan results (internal format)"],"output_types":["JSON report with violation array","each violation includes: WCAG criteria ID, severity level, description, remediation suggestion","summary statistics (total violations, breakdown by level)"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-equally-ai-mcp__cap_3","uri":"capability://data.processing.analysis.url.based.and.html.content.accessibility.scanning","name":"url-based and html content accessibility scanning","description":"Accepts both live URLs and raw HTML content as input to the accessibility audit tool, enabling scanning of deployed websites or local/in-development code without requiring deployment. The tool handles URL fetching, HTML parsing, and content normalization internally, supporting both public URLs and local file paths, allowing developers to audit accessibility at any stage of development.","intents":["I want to scan a live website URL for accessibility issues without downloading it locally","I need to audit HTML code snippets or local files before deploying to production","I want to check accessibility of dynamically generated content by passing raw HTML","I need to integrate accessibility scanning into a development workflow without deployment"],"best_for":["developers auditing live websites or staging environments","teams scanning local code during development before deployment","CI/CD pipelines that need to audit HTML artifacts without full deployment"],"limitations":["URL scanning requires network access — cannot scan internal/private URLs without proxy configuration","HTML content scanning is static — cannot detect issues in JavaScript-rendered content or dynamic DOM changes","No support for authenticated URLs — cannot scan pages behind login without session token handling","Large HTML files may timeout — no streaming or chunked processing for very large documents"],"requires":["valid URL (http/https) or raw HTML string","network access for URL scanning","HTML parser library (built into equally-ai-mcp)"],"input_types":["URL (string, http/https)","HTML content (string, raw markup)","optional: encoding specification"],"output_types":["accessibility scan results (JSON)","parsed DOM structure (internal)","violation list with line numbers (where applicable)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-equally-ai-mcp__cap_4","uri":"capability://tool.use.integration.mcp.server.lifecycle.management.and.client.communication","name":"mcp server lifecycle management and client communication","description":"Implements the MCP server protocol to handle client connections, tool invocation requests, and response serialization according to the MCP specification. The server manages request/response cycles, error handling, and protocol-level communication with MCP clients (Claude, Cline, custom hosts), ensuring reliable tool availability and proper error propagation through the MCP transport layer.","intents":["I want the accessibility audit tool to be reliably available to my MCP client","I need proper error handling and error messages when accessibility scans fail","I want the tool to handle concurrent requests from multiple LLM clients","I need the MCP server to gracefully handle connection drops and reconnections"],"best_for":["MCP client developers integrating equally-ai-mcp as a server dependency","teams running equally-ai-mcp in production with multiple concurrent LLM clients","developers debugging MCP protocol issues or tool invocation failures"],"limitations":["No built-in load balancing — single server instance may bottleneck under high concurrent load","Error messages are limited by MCP protocol — cannot stream large error logs or debugging information","No persistent state — server restarts lose any in-flight request context","MCP protocol overhead adds latency — each tool invocation incurs serialization/deserialization cost"],"requires":["Node.js 16+ runtime","@modelcontextprotocol/sdk library","MCP client implementation that supports stdio or network transport"],"input_types":["MCP protocol messages (JSON-RPC format)"],"output_types":["MCP protocol responses (JSON-RPC format)","tool invocation results","error responses with MCP error codes"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-equally-ai-mcp__cap_5","uri":"capability://data.processing.analysis.accessibility.compliance.level.filtering.a.aa.aaa","name":"accessibility compliance level filtering (a, aa, aaa)","description":"Allows filtering audit results by WCAG conformance level (A, AA, or AAA) to focus on specific compliance targets. The tool can be configured to report only violations at a specified level or above, enabling teams to prioritize fixes based on their compliance requirements and gradually improve accessibility maturity from Level A to AAA.","intents":["I want to focus on Level AA compliance violations and ignore Level A issues","I need to filter audit results to show only AAA-level accessibility requirements","I want to gradually improve accessibility from Level A to AA to AAA","I need to generate compliance reports for specific WCAG levels"],"best_for":["teams with specific WCAG compliance targets (e.g., government sites requiring AA)","organizations gradually improving accessibility maturity","accessibility teams prioritizing fixes by compliance level"],"limitations":["Filtering is post-scan — all violations are detected regardless of level, then filtered in output","No mixed-level reporting — cannot easily show 'Level A violations + critical Level AA issues'","Level definitions are static — cannot customize which criteria map to which levels"],"requires":["WCAG 2.1 criteria database with level mappings (built-in)","filter parameter in audit request (optional, defaults to all levels)"],"input_types":["conformance level filter: 'A' | 'AA' | 'AAA' (optional)"],"output_types":["filtered violation list","violations matching specified level and above"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":27,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ for MCP server runtime","MCP client implementation (Claude Desktop, Cline, or custom MCP host)","Valid URL or raw HTML content as input","Network access to target URLs if scanning external sites","MCP protocol implementation (typically Node.js with @modelcontextprotocol/sdk)","JSON schema validation library (built into most MCP implementations)","MCP client that supports tool discovery (Claude, Cline, custom hosts)","accessibility scanning engine (integrated with equally-ai-mcp)","WCAG 2.1 criteria database (internal to the tool)","remediation suggestion templates (built-in or configurable)"],"failure_modes":["MCP protocol overhead adds latency compared to direct API calls — each audit request requires MCP serialization/deserialization","Audit scope limited to static HTML analysis — cannot detect dynamic JavaScript-rendered accessibility issues without headless browser integration","No built-in caching of audit results — repeated scans of identical URLs incur full re-analysis cost","Requires MCP-compatible client (Claude, Cline, etc.) — cannot be used as standalone REST API","Schema is static — cannot dynamically adjust parameters based on runtime capabilities or feature flags","No versioning mechanism for tool schema — breaking changes require client-side updates","Schema validation occurs only at MCP protocol level — business logic validation (e.g., valid WCAG levels) must be implemented server-side","Remediation suggestions are template-based — may not account for complex design patterns or custom components","Severity classification is rule-based — does not incorporate user impact assessment or real-world accessibility testing","WCAG mapping is limited to 2.1 standard — does not include emerging standards like WCAG 3.0 or EN 301 549","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.22,"ecosystem":0.48000000000000004,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-05-03T14:24:00.018Z","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=npm-equally-ai-mcp","compare_url":"https://unfragile.ai/compare?artifact=npm-equally-ai-mcp"}},"signature":"00y3BEl2sbpEYwIdDrba6M7UKLiuHgXGrF9nwEx58sHmsySwVkgea0l+SMa6pGXPYOUCLtzeHrzyhy6CO9dIDA==","signedAt":"2026-06-20T16:15:14.796Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-equally-ai-mcp","artifact":"https://unfragile.ai/npm-equally-ai-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=npm-equally-ai-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}