Opik
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
MCP server · by comet-ml
About
Opik is an MCP server published by comet-ml. Marketplaces we read that list it: 2 (Official MCP Registry, Docker MCP Catalog). The last change we recorded was on 2026-10-12. As of our marketplace pass on 2026-10-12.
What it asks for
- Runs remotely
- Runs on your machine
- Secrets: 1
- Settings: 4
- Tools: 13
Tools it declares: 13. As declared on: Docker MCP Catalog.
add-trace-feedbackcreate-projectcreate-promptget-prompt-versionget-promptsget-trace-by-idget-trace-statsget-trace-threadslist-projectslist-tracesopik-integration-docssave-prompt-version
Show the remaining 1
search-traces
Requires: OPIK_API_KEY (secret)
What it declares, asks for and runs, in full
Only install plugins from developers you trust. We list what marketplaces publish and do not test plugins.
Works with
- Claude Code
- Codex
- Cursor
- VS Code
- Copilot CLI
A one-click link opens the client, which asks you to confirm before it adds the server.
From the marketplaces that list it and the MCP transport it declares, as each client documents them. We do not test plugins.
Connect
Commands and configs built only from what its marketplaces declare. We do not run them for you and do not test plugins.
As a remote MCP server
Built from what Official MCP Registry declares.
claude mcp add --transport http opik-mcp https://www.comet.com/opik/api/v1/mcp[mcp_servers.opik-mcp]
url = "https://www.comet.com/opik/api/v1/mcp"{
"mcpServers": {
"opik-mcp": {
"url": "https://www.comet.com/opik/api/v1/mcp"
}
}
}Where it is published
| Marketplace | Status | Version | Figures | Verified | First seen |
|---|---|---|---|---|---|
| Official MCP Registry (Open the registry record) | Listed | 3.0.5 | Forks (GitHub): 38 Stars (GitHub): 221 |
Not marked | |
| Docker MCP Catalog (Open on Docker Hub) | Listed | sha256:0e0d7d33d5eb | Forks (GitHub): 38 Pulls (Docker Hub): 16 932 Stars (Docker Hub): 1 Stars (GitHub): 221 |
Not marked |
Each figure is the marketplace's own and is never added up across marketplaces. A marketplace that publishes no figure shows none: no number is not zero.
What changed
Nothing has moved on this plugin since we started watching it.
Similar plugins
Products whose own names, descriptions, tools and skills are closest in meaning to this one, on every marketplace we read. Closeness is ranked within this list only.
-
Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Run AI agent evaluations on your own model keys, and publish runs others can review and re-run.
-
Structured observability for AI agents. Trace steps, decisions, and errors. MCP server + CLI viewer.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Pay-per-call AI evaluation MCP server. Score LLM outputs against benchmark rubrics via Workers AI.
-
pramana-mcp io.github.loopg/pramana-mcp
Read your recorded AI agent runs, and what changed when you swapped a model or prompt.
-
Mini Data Engine Runtime Copilot
MCP runtime copilot for health checks, regressions, explainability, and operational memory.
-
Evaluate, benchmark, and simulate AI agents on the VerifyAX agent-evaluation platform.
-
llm-observability-orchestration-agent-langchain-community ai.getvda/llm-observability-orchestration-agent-langchain-community
LLM Observability & Orchestration Agent (LangChain Community)
Similar plugins by marketplace
The same question asked of one marketplace at a time: is there an analog of this plugin there?
Has a listing on Claude Code: claude-plugins-community (5)
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
AI agent evaluation sandbox for Claude Code. Holdout scenario testing with Doer/Judge/Adversary/Observer roles, probabilistic satisfaction scoring, and append-only JSONL audit…
-
Context engineering plugin for Claude Code — real-time prompt scoring, RLM adaptive weights, and token optimization. Scores every tool use across 5 dimensions (token utilization…
-
Agent Trace Triage is a Claude Code plugin for developers building agentic AI systems (LangGraph, CrewAI, custom tool loops, MCP agents). When an agent run fails, stuck in a loop…
-
Autonomous experiment loop for Claude Code. Run an endless optimize-measure-keep/discard cycle on any optimization target: LLM training loss, test speed, bundle size, build time…
Has a listing on Claude Code: claude-plugins-official (5)
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Skills for tracing, evaluating, and improving AI agents with MLflow. Supports the full agent improvement loop: instrument → trace → evaluate → iterate → validate.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
OpenTelemetry observability for Claude Code sessions. Captures tool calls, LLM invocations, token usage, and errors as OTel traces. Send telemetry to Dash0 or any…
Has a listing on Claude: knowledge-work-plugins (5)
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
-
AI-first project auditor and re-engineer based on the 9 design principles and 7 design patterns from the TechWolf AI-First Bootcamp
-
A suite of agent skills for the full GrowthBook feature flag and experimentation lifecycle.
Has a listing on Codex: openai-curated (openai/plugins) (5)
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
Available for US1 customers only. Analyze, investigate, and act on your Datadog telemetry directly from ChatGPT using natural language. Ask questions about your production…
-
Answer product and business questions with data
Has a listing on Community GitHub marketplaces (5)
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Dash0 Observability
OpenTelemetry observability for OpenAI Codex sessions. Captures prompts, tool calls, MCP calls, sub-agent activity, and token usage as OTel traces.
-
Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.
-
Endor Labs AI Plugins (Legacy)
Legacy Claude Code plugin id for Endor Labs Agent Kit workflows.
Has a listing on Copilot CLI: github/awesome-copilot (5)
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
Visualizes live session AI-credit usage as a Pac-Man board with pellets, ghosts, fruit milestones, and game-over limits.
-
See your local Copilot token usage by day, model, and session, and get tips to use it more efficiently.
-
Three-layer verification pipeline for AI output. Extracts claims, finds sources, and flags hallucination risks so humans can verify before acting.
-
Safe BLE diagnostics, evidence workflows, and guarded automation for AI agents.
Has a listing on Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
workiq
Query Microsoft 365 data with natural language — emails, meetings, documents, Teams messages, and more.
-
model-apps
Build and deploy Power Apps generative pages for model-driven apps with specialist agents for planning, entity creation, and parallel code generation. Requires PAC CLI >= 2.7.0…
-
workiq-productivity
WorkIQ productivity skills powered by the local WorkIQ CLI — read-only insights across email, meetings, calendar, Teams, SharePoint, projects, and people.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
Has a listing on Cursor: cursor/plugins (5)
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
Track AI visibility, sentiment, and citations.
-
Incremental transcript-driven memory updates for AGENTS.md using high-signal bullet points only.
-
Inspect and manage feature gates, experiments, dynamic configs, and metrics.
-
Work with PostHog from chat: query product analytics and run SQL, manage feature flags and experiments, triage error tracking issues, and review session replays, surveys, and…
Has a listing on Docker MCP Catalog (5)
-
Wayfound’s MCP server allows business users to govern, supervise, and improve AI Agents.
-
Analyze documents, images, videos, and audio.
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
The Official Model Context Protocol (MCP) server for Kagi Search & other tools.
-
Tools for interacting with Hugging Face models, datasets, research papers, and more.
Has a listing on Official MCP Registry (5)
-
Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
-
Run AI agent evaluations on your own model keys, and publish runs others can review and re-run.
-
Structured observability for AI agents. Trace steps, decisions, and errors. MCP server + CLI viewer.
-
Pay-per-call AI evaluation MCP server. Score LLM outputs against benchmark rubrics via Workers AI.
-
pramana-mcp io.github.loopg/pramana-mcp
Read your recorded AI agent runs, and what changed when you swapped a model or prompt.
Found by meaning, not by shared code or a shared repository: similar plugins stay separate products, and this is not a review or a recommendation.
Is this your plugin?
Add it to your projects and prove you maintain it with a file in its repository, a file on your domain or a DNS record. You get alerts when a marketplace lists it, drops it, changes its verified mark or what it asks for, and its remote endpoint goes on monitoring as a web service.
Data comes from the Official MCP Registry (registry.modelcontextprotocol.io), CC0 1.0. Data comes from the Docker MCP Catalog (desktop.docker.com/mcp/catalog) and Docker Hub. Figures come from our own regular passes over the marketplaces, last read on . We publish no contact details for plugin publishers.