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Uses MCP's request-response messaging pattern to translate client tool calls into ChainLens API operations, handling schema validation, error mapping, and response serialization across the protocol boundary.","intents":["I want to use ChainLens data discovery directly from Claude Desktop without switching applications","I need to integrate ChainLens seller discovery into my MCP-compatible AI agent framework","I want to expose ChainLens capabilities as standardized tools that any MCP client can consume"],"best_for":["Claude Desktop users needing ChainLens integration","AI agent developers building multi-tool orchestration systems","Teams standardizing on MCP for LLM tool access"],"limitations":["Limited to MCP protocol capabilities — no streaming responses for long-running queries","Requires MCP client support; not compatible with REST-only or non-MCP tools","No built-in caching of MCP server state — each request hits ChainLens API directly"],"requires":["Node.js 16+ (typical MCP server runtime)","MCP client compatible with MCP 1.0+ specification","ChainLens API credentials or access token","Claude Desktop 0.0.1+ or compatible MCP client"],"input_types":["JSON-RPC 2.0 requests (MCP protocol format)","Tool invocation parameters (seller queries, job IDs, data request filters)"],"output_types":["JSON-RPC 2.0 responses","Structured seller data (name, location, capabilities)","Job status objects (state, progress, results)","Data request confirmations"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_1","uri":"capability://search.retrieval.seller.discovery.and.filtering.via.mcp.tool.interface","name":"seller discovery and filtering via mcp tool interface","description":"Exposes ChainLens seller discovery as an MCP tool that accepts filter parameters (location, capabilities, reputation metrics) and returns paginated seller profiles. Implements query parameter validation, result ranking/sorting, and structured response formatting compatible with MCP's tool result schema, allowing agents to programmatically search and evaluate data providers.","intents":["I need to find data sellers matching specific geographic or capability criteria","I want my AI agent to autonomously discover and rank available data providers","I need to integrate seller discovery into a larger data acquisition workflow"],"best_for":["Data acquisition teams automating supplier discovery","AI agents building dynamic data pipelines","Web3 applications needing decentralized data provider lookup"],"limitations":["Seller filtering is limited to ChainLens's indexed attributes — custom metadata not queryable","No real-time seller availability status — data may be stale by seconds to minutes","Pagination limited to standard offset/limit patterns; no cursor-based pagination for large result sets"],"requires":["Valid ChainLens API credentials","MCP client with tool invocation support","Network access to ChainLens backend"],"input_types":["Filter parameters: location (string), capabilities (array), min_reputation (number), limit (number), offset (number)"],"output_types":["Seller profiles: {id, name, location, capabilities, reputation_score, contact_info}","Pagination metadata: {total_count, returned_count, has_more}"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_2","uri":"capability://automation.workflow.data.request.submission.and.tracking.via.mcp","name":"data request submission and tracking via mcp","description":"Provides an MCP tool for submitting data requests to discovered sellers and retrieving request status/results. Implements request creation (with seller ID, data schema, pricing negotiation), asynchronous job tracking (polling or webhook-based status updates), and result retrieval. Handles request state transitions (pending, accepted, processing, completed, failed) and integrates with ChainLens's job queue system.","intents":["I want to programmatically request data from a specific seller and track fulfillment","I need my agent to submit multiple data requests in parallel and wait for results","I want to integrate data request workflows into a larger pipeline without manual intervention"],"best_for":["Automated data acquisition pipelines","AI agents orchestrating multi-seller data collection","Applications requiring asynchronous data fulfillment workflows"],"limitations":["No built-in timeout handling — long-running requests require external timeout management","Polling-based status checks add latency; webhook support depends on ChainLens backend capability","Request cancellation not supported — submitted requests cannot be revoked","No transaction rollback — failed requests don't automatically trigger fallback sellers"],"requires":["Valid ChainLens API credentials with data request permissions","Seller ID from prior discovery operation","MCP client supporting async tool result handling","Network connectivity to ChainLens backend"],"input_types":["Request creation: {seller_id, data_schema, price_limit, delivery_deadline}","Status check: {request_id}"],"output_types":["Request confirmation: {request_id, seller_id, status, created_at}","Status update: {request_id, status, progress_percent, estimated_completion}","Result retrieval: {request_id, data_payload, delivery_timestamp, seller_signature}"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_3","uri":"capability://automation.workflow.job.status.polling.and.result.retrieval","name":"job status polling and result retrieval","description":"Implements a dedicated MCP tool for checking the status of submitted data requests and retrieving completed results. Polls ChainLens's job queue system using request IDs, returns structured status objects (state, progress percentage, error messages), and handles result deserialization when jobs complete. Supports both synchronous polling (blocking until completion) and asynchronous status checks (return current state without waiting).","intents":["I need to check if my data request has completed without blocking my agent","I want to retrieve the actual data payload once a request is fulfilled","I need to handle job failures and retry with alternative sellers"],"best_for":["Long-running data pipelines requiring non-blocking status checks","Agents managing multiple concurrent data requests","Applications with strict latency requirements (can't afford blocking polls)"],"limitations":["Polling interval is fixed or client-controlled — no server-side push notifications","Status granularity limited to ChainLens's job states; no sub-task progress visibility","Result retrieval requires separate API call after job completion — no streaming","No automatic retry on transient failures — client must implement retry logic"],"requires":["Valid request_id from prior data request submission","ChainLens API credentials","MCP client supporting repeated tool invocations"],"input_types":["Job status query: {request_id, include_progress: boolean}","Result retrieval: {request_id, format: 'json'|'csv'|'parquet'}"],"output_types":["Status response: {request_id, status: 'pending'|'processing'|'completed'|'failed', progress_percent, estimated_time_remaining}","Error response: {request_id, status: 'failed', error_code, error_message, retry_after_seconds}","Result payload: {request_id, data, delivery_timestamp, seller_signature, format}"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_4","uri":"capability://tool.use.integration.mcp.tool.schema.definition.and.validation","name":"mcp tool schema definition and validation","description":"Defines and validates the JSON Schema for all exposed ChainLens tools (seller discovery, data requests, job status), ensuring that Claude and MCP clients can introspect available operations, required parameters, and response formats. Implements schema validation on incoming requests and outgoing responses, providing clear error messages for malformed inputs. Handles type coercion (string to number, array flattening) and default parameter injection.","intents":["I want Claude to understand what ChainLens operations are available and their parameters","I need validation to catch malformed requests before they hit the ChainLens API","I want clear error messages when my agent provides invalid parameters"],"best_for":["MCP server developers ensuring protocol compliance","Teams building robust agent systems with strict input validation","Applications requiring audit trails of all tool invocations"],"limitations":["Schema validation adds ~5-10ms latency per request","Custom validation rules beyond JSON Schema not supported — must be implemented in tool handlers","Schema updates require server restart; no hot-reload capability","No schema versioning — breaking changes require client updates"],"requires":["JSON Schema 2020-12 compatible validator (e.g., ajv)","MCP server implementation with schema registration"],"input_types":["JSON Schema definitions for each tool","Tool invocation requests with parameters"],"output_types":["Validated parameter objects","Validation error responses with field-level details","Schema introspection responses for MCP clients"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_5","uri":"capability://tool.use.integration.error.handling.and.response.normalization.across.mcp.protocol","name":"error handling and response normalization across mcp protocol","description":"Implements a unified error handling layer that translates ChainLens API errors (rate limits, authentication failures, seller unavailable) into MCP-compliant error responses with consistent structure. Maps HTTP status codes to MCP error codes, enriches errors with retry guidance (Retry-After headers, exponential backoff recommendations), and normalizes all responses (success and failure) into MCP's standard JSON-RPC format with proper error objects.","intents":["I want my agent to handle ChainLens errors gracefully without crashing","I need to know when to retry a failed request and how long to wait","I want consistent error messages across all ChainLens tools"],"best_for":["Production agents requiring robust error recovery","Teams building resilient data pipelines with automatic retry logic","Applications with strict SLA requirements"],"limitations":["Error enrichment depends on ChainLens API response quality — some errors may lack detail","Retry recommendations are heuristic-based; no guarantee of success on retry","No circuit breaker pattern — repeated failures don't automatically disable the tool","Timeout errors may not include estimated recovery time"],"requires":["MCP server with JSON-RPC error handling","ChainLens API error documentation"],"input_types":["ChainLens API error responses (HTTP status + body)","MCP tool invocation requests"],"output_types":["MCP error objects: {code: number, message: string, data: {retry_after, error_type, details}}","Normalized success responses: {result: {...}, metadata: {execution_time_ms}}"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_6","uri":"capability://safety.moderation.authentication.and.credential.management.for.chainlens.api.access","name":"authentication and credential management for chainlens api access","description":"Manages ChainLens API credentials (API keys, tokens) securely within the MCP server process, handling credential injection into outgoing requests, token refresh logic, and credential rotation. Supports multiple authentication methods (API key, OAuth2 bearer token) and implements credential caching to avoid repeated lookups. Provides secure credential storage patterns (environment variables, credential files with restricted permissions) and logs authentication failures without exposing secrets.","intents":["I want to securely configure ChainLens credentials for my MCP server without hardcoding them","I need my MCP server to automatically refresh expired tokens","I want to rotate credentials without restarting the server"],"best_for":["Production deployments requiring secure credential management","Teams with credential rotation policies","Multi-tenant MCP server deployments"],"limitations":["Credentials stored in process memory — vulnerable to memory dumps","No built-in credential rotation scheduling — manual or external orchestration required","Token refresh logic depends on ChainLens API's token expiration semantics","No audit logging of credential access — compliance teams may require external logging"],"requires":["Environment variable or credential file with ChainLens API key","Node.js process with restricted file permissions (for credential files)","ChainLens API documentation for authentication method"],"input_types":["Credential configuration: {api_key} or {oauth_token}","Tool invocation requests (credentials injected automatically)"],"output_types":["Authenticated HTTP requests to ChainLens API","Authentication error responses (401, 403)"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-chain-lensmcp-tool__cap_7","uri":"capability://automation.workflow.request.response.logging.and.observability.hooks","name":"request/response logging and observability hooks","description":"Provides structured logging of all MCP tool invocations, ChainLens API calls, and responses, enabling debugging and monitoring. Logs include request parameters (sanitized of sensitive data), response status, execution time, and error details. Implements observability hooks (timing instrumentation, error counters) compatible with standard logging frameworks (Winston, Pino) and monitoring systems (Prometheus, DataDog). Supports log level configuration (debug, info, warn, error) for production vs. development environments.","intents":["I want to debug why a specific tool invocation failed","I need to monitor MCP server performance and ChainLens API latency","I want to audit all data requests for compliance purposes"],"best_for":["Production MCP servers requiring observability","Teams with compliance or audit requirements","Developers debugging agent behavior"],"limitations":["Logging adds ~2-5ms overhead per request","Sensitive data (API keys, personal data in requests) must be manually redacted","Log storage and retention are external responsibilities — server only emits logs","No built-in log aggregation — requires external ELK, Splunk, or similar"],"requires":["Logging framework (Winston, Pino, or compatible)","Log storage backend (file, cloud logging service)","Optional: monitoring system for metrics collection"],"input_types":["MCP tool invocation requests","ChainLens API responses","Error objects"],"output_types":["Structured log entries: {timestamp, level, tool_name, request_id, status, execution_time_ms, error_code}","Metrics: request_count, error_rate, latency_percentiles"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":34,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ (typical MCP server runtime)","MCP client compatible with MCP 1.0+ specification","ChainLens API credentials or access token","Claude Desktop 0.0.1+ or compatible MCP client","Valid ChainLens API credentials","MCP client with tool invocation support","Network access to ChainLens backend","Valid ChainLens API credentials with data request permissions","Seller ID from prior discovery operation","MCP client supporting async tool result handling"],"failure_modes":["Limited to MCP protocol capabilities — no streaming responses for long-running queries","Requires MCP client support; not compatible with REST-only or non-MCP tools","No built-in caching of MCP server state — each request hits ChainLens API directly","Seller filtering is limited to ChainLens's indexed attributes — custom metadata not queryable","No real-time seller availability status — data may be stale by seconds to minutes","Pagination limited to standard offset/limit patterns; no cursor-based pagination for large result sets","No built-in timeout handling — long-running requests require external timeout management","Polling-based status checks add latency; webhook support depends on ChainLens backend capability","Request cancellation not supported — submitted requests cannot be revoked","No transaction rollback — failed requests don't automatically trigger fallback sellers","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.41,"ecosystem":0.5000000000000001,"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":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-05-03T14:23:56.659Z","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-chain-lensmcp-tool","compare_url":"https://unfragile.ai/compare?artifact=npm-chain-lensmcp-tool"}},"signature":"D/A8mIPKf1RCNxicrE98Vq2gtxcLjw634CbF4fsmTvt+omJIntIR9kwdYgCIliFOPie4JwaNmS2B7rB3f/xDAg==","signedAt":"2026-06-21T14:30:22.236Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-chain-lensmcp-tool","artifact":"https://unfragile.ai/npm-chain-lensmcp-tool","verify":"https://unfragile.ai/api/v1/verify?slug=npm-chain-lensmcp-tool","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"}}