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Uses TypeScript/Node.js to handle MCP transport layer (stdio, SSE, or WebSocket), request routing, and resource serialization, enabling any MCP-compatible client (Claude Desktop, IDEs, agents) to interact with Opik without custom integrations.","intents":["Connect Opik to Claude Desktop or other MCP clients without writing custom plugins","Enable LLM agents to query Opik prompts, projects, and traces as first-class resources","Expose Opik metrics and trace data to IDE-integrated AI assistants"],"best_for":["Teams using Opik for LLM observability who want IDE-native access","Developers building multi-tool AI agents that need unified observability context","Organizations standardizing on MCP for AI tool integration"],"limitations":["MCP transport overhead adds ~50-100ms per request compared to direct HTTP calls","Requires MCP-compatible client; not compatible with non-MCP tools or older IDE versions","No built-in caching of Opik responses — each MCP request hits Opik API directly","Limited to read-only operations for most resources; write operations may be restricted by MCP schema"],"requires":["Node.js 16+ (TypeScript runtime)","Opik API endpoint and valid API credentials","MCP-compatible client (Claude Desktop 0.4+, or custom MCP client)","Network access to Opik backend"],"input_types":["MCP resource requests (JSON-RPC 2.0)","Tool invocation payloads with parameters","Query filters for prompts/traces/projects"],"output_types":["MCP resource objects (prompts, projects, traces, metrics)","Tool execution results (JSON)","Structured trace and metric data"],"categories":["tool-use-integration","mcp-server"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_1","uri":"capability://memory.knowledge.prompt.management.and.retrieval.via.mcp.resources","name":"prompt management and retrieval via mcp resources","description":"Exposes Opik's prompt library as queryable MCP resources, allowing clients to list, search, and retrieve prompts by name, version, or metadata. Implements resource handlers that call Opik's prompt API endpoints, serialize prompt definitions (template, variables, metadata) into MCP resource format, and support filtering/pagination for large prompt libraries.","intents":["Query available prompts in Opik from within Claude Desktop or IDE","Retrieve a specific prompt version for use in an LLM agent","Search prompts by name or tag without leaving the IDE"],"best_for":["Teams managing large prompt libraries who want IDE-native access","Developers building agents that need to dynamically load prompts from Opik","Non-technical users who want to browse prompts without CLI or web UI"],"limitations":["Read-only access; prompt creation/editing must happen in Opik UI or API","No real-time sync — prompt updates in Opik may take seconds to reflect in MCP","Pagination required for libraries >1000 prompts; no full-text search, only metadata filtering"],"requires":["Opik instance with prompts already created","Valid Opik API key with read permissions on prompts","MCP client with resource browsing capability"],"input_types":["Prompt name or ID (string)","Filter parameters (version, tags, metadata)","Pagination tokens"],"output_types":["Prompt objects with template, variables, metadata","Prompt version history","Structured prompt metadata"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_2","uri":"capability://search.retrieval.trace.and.span.data.retrieval.with.filtering","name":"trace and span data retrieval with filtering","description":"Implements MCP tools and resources to query Opik's trace database, returning structured trace hierarchies (spans, metadata, metrics) filtered by project, time range, status, or custom attributes. Uses Opik's trace query API to fetch paginated results and serializes nested span structures into MCP-compatible JSON, enabling agents and IDEs to inspect LLM execution history.","intents":["Retrieve execution traces for a specific LLM call to debug behavior","Query traces by project and time range to analyze performance trends","Access span-level details (latency, tokens, errors) for optimization"],"best_for":["Developers debugging LLM agent behavior in real-time","Teams analyzing trace data for performance optimization","Agents that need to introspect their own execution history"],"limitations":["Large traces (>100 spans) may exceed MCP message size limits; requires streaming or pagination","No aggregation or statistical analysis — raw trace retrieval only","Filtering is limited to Opik's query API capabilities; complex custom queries require post-processing","Trace data is immutable; cannot modify or delete traces via MCP"],"requires":["Opik instance with active traces","Valid Opik API key with read permissions on traces","Project ID or name to filter traces"],"input_types":["Project ID or name (string)","Time range (ISO 8601 timestamps)","Filter criteria (status, span name, custom attributes)","Pagination parameters"],"output_types":["Trace objects with nested span hierarchies","Span metadata (latency, tokens, status, errors)","Custom attributes and metrics per span"],"categories":["search-retrieval","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_3","uri":"capability://search.retrieval.project.and.workspace.enumeration","name":"project and workspace enumeration","description":"Provides MCP resources to list and browse Opik projects and workspaces, returning metadata (name, description, creation date, trace count) for each project. Implements resource handlers that call Opik's project listing API and serialize results into MCP resource format, enabling clients to discover and select projects for trace/prompt queries.","intents":["List all available projects in Opik to select which one to query","Discover project metadata (description, owner, trace count) without web UI","Enable agents to dynamically select the correct project context"],"best_for":["Multi-project teams who need to switch project context frequently","Agents that operate across multiple Opik projects","Users exploring Opik data without access to the web dashboard"],"limitations":["Read-only; project creation/deletion must happen in Opik UI","No real-time sync — new projects may take seconds to appear in MCP","Limited metadata returned; detailed project settings require Opik API direct access"],"requires":["Opik instance with at least one project","Valid Opik API key with read permissions on projects"],"input_types":["Optional: filter by project name or owner"],"output_types":["Project objects with name, description, metadata","Project IDs and workspace associations","Trace count and other aggregate metrics per project"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_4","uri":"capability://data.processing.analysis.metrics.and.aggregation.data.exposure","name":"metrics and aggregation data exposure","description":"Implements MCP tools to retrieve aggregated metrics from Opik (latency percentiles, token usage, error rates, cost estimates) grouped by project, span type, or time bucket. Calls Opik's metrics API to compute aggregations and returns structured metric objects with time-series data, enabling agents and IDEs to analyze performance trends without manual dashboard inspection.","intents":["Get latency and token usage statistics for a project to identify bottlenecks","Retrieve error rates and failure patterns for debugging","Access cost estimates for LLM calls to track spending"],"best_for":["Teams monitoring LLM performance and cost in production","Developers optimizing prompt/model choices based on metrics","Agents that need to make decisions based on performance data"],"limitations":["Metrics are computed on-demand; large time ranges may be slow (>5s latency)","No custom metric definitions — limited to Opik's built-in metrics (latency, tokens, cost, errors)","Aggregation granularity is fixed (hourly, daily); no sub-minute metrics","Historical data retention depends on Opik plan; older data may be unavailable"],"requires":["Opik instance with active traces to compute metrics from","Valid Opik API key with read permissions on metrics","Project ID to scope metrics"],"input_types":["Project ID (string)","Time range (ISO 8601 timestamps)","Grouping dimension (project, span type, model, etc.)","Metric type (latency, tokens, cost, errors)"],"output_types":["Metric objects with aggregated values (mean, p50, p95, p99)","Time-series metric data","Breakdown by dimension (model, span type, etc.)"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_5","uri":"capability://tool.use.integration.ide.and.claude.desktop.client.integration","name":"ide and claude desktop client integration","description":"Implements MCP server transport handlers (stdio, SSE, WebSocket) and client discovery mechanisms to integrate Opik with Claude Desktop, VS Code, and other MCP-compatible IDEs. Handles MCP protocol handshake, capability negotiation, and resource/tool registration, allowing IDEs to automatically discover and use Opik's prompts, traces, and metrics without manual configuration.","intents":["Enable Claude Desktop to access Opik data natively via MCP","Integrate Opik into VS Code via MCP extension","Allow any MCP-compatible IDE to query Opik without custom plugins"],"best_for":["Teams using Claude Desktop for AI-assisted development","VS Code users who want Opik integration without custom extensions","Organizations standardizing on MCP for tool integration"],"limitations":["Requires MCP-compatible client; not compatible with older IDE versions or non-MCP tools","Transport layer (stdio, SSE, WebSocket) must be configured per client; no auto-discovery","IDE-specific features (syntax highlighting, inline suggestions) depend on client implementation","Authentication is delegated to Opik API key; no IDE-native auth UI"],"requires":["Claude Desktop 0.4+ or MCP-compatible IDE","Node.js 16+ to run MCP server","Valid Opik API credentials","Network connectivity to Opik backend"],"input_types":["MCP client configuration (transport, server URL)","Opik API credentials (API key or OAuth token)"],"output_types":["MCP resource and tool listings","IDE-compatible resource representations"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_6","uri":"capability://tool.use.integration.tool.based.function.calling.for.opik.operations","name":"tool-based function calling for opik operations","description":"Exposes Opik operations (query traces, retrieve prompts, fetch metrics) as MCP tools with JSON schema definitions, enabling LLM agents to invoke these operations via function calling. Implements tool handlers that parse tool invocation payloads, call corresponding Opik API endpoints, and return structured results, allowing agents to autonomously interact with Opik without explicit API knowledge.","intents":["Enable agents to query Opik traces autonomously during execution","Allow agents to retrieve and use prompts from Opik dynamically","Let agents analyze metrics to make optimization decisions"],"best_for":["Developers building multi-step LLM agents that need Opik observability context","Teams using agents for automated debugging or optimization","Agents that need to introspect their own performance via Opik"],"limitations":["Tool invocation adds latency (~100-200ms per call) due to MCP round-trip","No built-in caching of tool results; repeated queries hit Opik API each time","Tool schemas are static; dynamic schema generation based on Opik API changes requires server restart","Error handling is basic; complex error scenarios may require agent-side retry logic"],"requires":["MCP-compatible LLM client (Claude, custom agent framework)","Valid Opik API credentials","Tool schema definitions in MCP server"],"input_types":["Tool invocation payloads with parameters (JSON)","Query filters and pagination parameters"],"output_types":["Tool execution results (JSON)","Structured Opik data (traces, prompts, metrics)","Error messages with diagnostic info"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_7","uri":"capability://safety.moderation.authentication.and.credential.management","name":"authentication and credential management","description":"Implements credential handling for Opik API access, supporting API key-based authentication and optional OAuth token exchange. Stores credentials securely (environment variables, config files, or secure storage) and injects them into all Opik API requests made by the MCP server, ensuring authenticated access without exposing credentials to clients.","intents":["Securely authenticate MCP server to Opik backend","Support multiple authentication methods (API key, OAuth)","Prevent credential leakage to MCP clients"],"best_for":["Teams with strict security requirements for credential management","Organizations using OAuth for centralized identity management","Multi-user environments where credentials must be isolated"],"limitations":["Credentials must be configured before server startup; no runtime credential rotation","No built-in credential refresh; OAuth tokens must be manually refreshed or server restarted","Credentials are stored in plaintext in environment or config files; requires OS-level security","No audit logging of credential usage; cannot track which clients accessed which resources"],"requires":["Valid Opik API key or OAuth credentials","Secure storage mechanism (environment variables, secure config file, or OS keystore)","Network access to Opik authentication endpoints (for OAuth)"],"input_types":["API key (string) or OAuth token (JWT)","Opik workspace/organization ID"],"output_types":["Authenticated HTTP headers for Opik API requests","Token validation status"],"categories":["safety-moderation","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github_mcp-comet-ml-opik-mcp__cap_8","uri":"capability://safety.moderation.error.handling.and.diagnostic.logging","name":"error handling and diagnostic logging","description":"Implements comprehensive error handling for MCP protocol errors, Opik API failures, and network issues, returning structured error responses to clients with diagnostic information. Includes optional debug logging to help troubleshoot integration issues, with configurable log levels and output destinations (stdout, files, external logging services).","intents":["Diagnose MCP server connectivity issues","Debug Opik API failures (rate limits, auth errors, timeouts)","Troubleshoot integration problems without direct server access"],"best_for":["DevOps teams deploying MCP server in production","Developers debugging integration issues","Teams with centralized logging infrastructure"],"limitations":["Logging adds overhead (~10-50ms per request); verbose logging can impact performance","Error messages may leak sensitive information (API URLs, project IDs); requires careful log sanitization","No built-in alerting; errors are logged but not actively monitored","Log retention depends on external logging infrastructure; local logs may be lost on server restart"],"requires":["Logging configuration (log level, output destination)","Optional: external logging service (e.g., Datadog, CloudWatch)"],"input_types":["Error events from MCP protocol or Opik API","Request/response metadata for context"],"output_types":["Structured error responses (JSON) to MCP clients","Diagnostic logs with timestamps and context"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":40,"verified":false,"data_access_risk":"high","permissions":["Node.js 16+ (TypeScript runtime)","Opik API endpoint and valid API credentials","MCP-compatible client (Claude Desktop 0.4+, or custom MCP client)","Network access to Opik backend","Opik instance with prompts already created","Valid Opik API key with read permissions on prompts","MCP client with resource browsing capability","Opik instance with active traces","Valid Opik API key with read permissions on traces","Project ID or name to filter traces"],"failure_modes":["MCP transport overhead adds ~50-100ms per request compared to direct HTTP calls","Requires MCP-compatible client; not compatible with non-MCP tools or older IDE versions","No built-in caching of Opik responses — each MCP request hits Opik API directly","Limited to read-only operations for most resources; write operations may be restricted by MCP schema","Read-only access; prompt creation/editing must happen in Opik UI or API","No real-time sync — prompt updates in Opik may take seconds to reflect in MCP","Pagination required for libraries >1000 prompts; no full-text search, only metadata filtering","Large traces (>100 spans) may exceed MCP message size limits; requires streaming or pagination","No aggregation or statistical analysis — raw trace retrieval only","Filtering is limited to Opik's query API capabilities; complex custom queries require post-processing","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.27115856385441606,"quality":0.43,"ecosystem":0.62,"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":"2026-05-24T12:16:22.064Z","last_scraped_at":"2026-05-03T14:23:38.364Z","last_commit":"2026-03-17T17:58:08Z"},"community":{"stars":203,"forks":30,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=mcp-comet-ml-opik-mcp","compare_url":"https://unfragile.ai/compare?artifact=mcp-comet-ml-opik-mcp"}},"signature":"8pPIZlZjEqweP+UauHRKcZBIg91lPmlT6qWN+/YhUAEB+EnN5pT00hwhAyS5sazIH+lkgHcPaFXLmEgBCngbDA==","signedAt":"2026-06-21T10:16:51.946Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/mcp-comet-ml-opik-mcp","artifact":"https://unfragile.ai/mcp-comet-ml-opik-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=mcp-comet-ml-opik-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"}}