/ Directorio / Playground / opik-mcp
● Comunidad comet-ml ⚡ Instantáneo

opik-mcp

por comet-ml · comet-ml/opik-mcp

Comet's official Opik MCP — manage prompts, projects, traces, and metrics of your LLM apps from Claude or Cursor without switching tabs.

Opik is an LLM observability platform (prompts, traces, evals, datasets). This official MCP gives your IDE/agent access to those primitives: list traces, pull prompts, create datasets, inspect metrics. Works with Opik Cloud or self-hosted.

Por qué usarlo

Características clave

Demo en vivo

Cómo se ve en la práctica

opik.replay ▶ listo
0/0

Instalar

Elige tu cliente

~/Library/Application Support/Claude/claude_desktop_config.json  · Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "opik": {
      "command": "npx",
      "args": [
        "-y",
        "opik-mcp"
      ],
      "_inferred": true
    }
  }
}

Abre Claude Desktop → Settings → Developer → Edit Config. Reinicia después de guardar.

~/.cursor/mcp.json · .cursor/mcp.json
{
  "mcpServers": {
    "opik": {
      "command": "npx",
      "args": [
        "-y",
        "opik-mcp"
      ],
      "_inferred": true
    }
  }
}

Cursor usa el mismo esquema mcpServers que Claude Desktop. La configuración del proyecto prevalece sobre la global.

VS Code → Cline → MCP Servers → Edit
{
  "mcpServers": {
    "opik": {
      "command": "npx",
      "args": [
        "-y",
        "opik-mcp"
      ],
      "_inferred": true
    }
  }
}

Haz clic en el icono MCP Servers de la barra lateral de Cline y luego en "Edit Configuration".

~/.codeium/windsurf/mcp_config.json
{
  "mcpServers": {
    "opik": {
      "command": "npx",
      "args": [
        "-y",
        "opik-mcp"
      ],
      "_inferred": true
    }
  }
}

Mismo formato que Claude Desktop. Reinicia Windsurf para aplicar.

~/.continue/config.json
{
  "mcpServers": [
    {
      "name": "opik",
      "command": "npx",
      "args": [
        "-y",
        "opik-mcp"
      ]
    }
  ]
}

Continue usa un array de objetos de servidor en lugar de un mapa.

~/.config/zed/settings.json
{
  "context_servers": {
    "opik": {
      "command": {
        "path": "npx",
        "args": [
          "-y",
          "opik-mcp"
        ]
      }
    }
  }
}

Añádelo a context_servers. Zed recarga en caliente al guardar.

claude mcp add opik -- npx -y opik-mcp

Un solo comando. Verifica con claude mcp list. Quita con claude mcp remove.

Casos de uso

Usos del mundo real: opik-mcp

Pull a production trace into your IDE to debug a bad LLM response

👤 LLM app developers ⏱ ~15 min intermediate

Cuándo usarlo: A user reports a wrong answer; the trace is in Opik; you want to inspect it without leaving Cursor.

Requisitos previos
  • Opik API key — comet.com/site > API Keys (or self-hosted admin)
Flujo
  1. Find the trace
    Search traces in project 'prod-chatbot' where output contains 'I cannot help with that'. Last 24h.✓ Copiado
    → Matching trace IDs + timestamps
  2. Inspect
    Open trace ID abc123. Show me the full message chain, tools called, and intermediate reasoning.✓ Copiado
    → Full trace object
  3. Form hypothesis
    Why might the model have refused? Compare this trace to a successful one on the same prompt template.✓ Copiado
    → Diff + hypothesis

Resultado: Faster trace-driven debugging without app-switching.

Errores comunes
  • PII in traces — Configure Opik's redaction before enabling MCP access broadly

Iterate on a prompt template with version tracking

👤 Prompt engineers ⏱ ~25 min advanced

Cuándo usarlo: You're tuning a system prompt and want each version saved to Opik for rollback.

Flujo
  1. Pull current version
    Get latest version of prompt 'support-agent-system'.✓ Copiado
    → Current prompt body
  2. Edit and commit
    Propose a change to handle escalations better. Show diff. Commit as a new version with message 'add escalation path'.✓ Copiado
    → Diff + new version ID
  3. Eval against dataset
    Run this new version against dataset 'support-eval-v1'. Compare pass rate vs previous version.✓ Copiado
    → Metric comparison

Resultado: Data-driven prompt changes, version-controlled.

Errores comunes
  • No guardrails — a regressive prompt becomes prod — Use Opik's experiment framework: don't promote until pass rate ≥ baseline

Generate a weekly LLM app health report

👤 Eng leads, LLM app PMs ⏱ ~30 min intermediate

Cuándo usarlo: You want a Monday-morning digest of cost, latency, error rate, and top failure categories.

Flujo
  1. Pull last week's metrics
    For project 'prod-chatbot': total traces, total tokens, avg latency p50/p95, error count — over last 7 days.✓ Copiado
    → Metrics block
  2. Classify failures
    Sample 20 failed traces. Cluster by failure mode. Rank clusters by frequency.✓ Copiado
    → Failure taxonomy
  3. Write the digest
    Compose a Markdown digest with the metrics and top 3 failure modes, ready for Slack.✓ Copiado
    → Shareable report

Resultado: Weekly LLM ops awareness without manual dashboard time.

Errores comunes
  • Metric drift as your app evolves — Version the report template; compare apples to apples week over week
Combinar con: notion

Combinaciones

Combínalo con otros MCPs para multiplicar por 10

opik + github

When a prompt regresses, open a GitHub issue with the failing trace

If pass rate drops >5% on 'support-eval-v1' vs last week, create a GitHub issue with the top 3 failing trace IDs.✓ Copiado
opik + notion

Publish weekly LLM health digest to Notion

Compose a Monday digest from last week's Opik metrics and create a Notion page in 'LLM Weekly'.✓ Copiado

Herramientas

Lo que expone este MCP

HerramientaEntradasCuándo llamarCoste
list_projects workspace_id? Navigate your workspace 1 API call
list_traces project, filter?, start?, end?, limit? Find traces by time range or content 1 API call
get_trace trace_id Deep-dive a single trace 1 API call
get_prompt name, version? Read a prompt for editing or use in code 1 API call
create_prompt_version name, template, message? Commit a new prompt iteration 1 API call
create_dataset name, items[] Build an eval dataset 1 API call
get_metrics project, metric, window Monitor cost / latency / quality 1 API call

Coste y límites

Lo que cuesta ejecutarlo

Cuota de API
Opik Cloud has per-plan limits; self-hosted is unlimited
Tokens por llamada
Trace listings 1k-5k tokens; single traces 500-3000
Monetario
Opik has a generous free tier; paid plans for scale. MCP itself is free (Apache 2.0).
Consejo
Use list_traces with a time window; never call without a range on a busy project.

Seguridad

Permisos, secretos, alcance

Ámbitos mínimos: Opik API key scope the workspace you intend to expose
Almacenamiento de credenciales: OPIK_API_KEY env var; HTTP transport uses Authorization: Bearer
Salida de datos: Traces may contain prompts/responses with PII — understand your Opik region and redaction setup
No conceder nunca: An admin-scope key to a shared dev machine

Resolución de problemas

Errores comunes y soluciones

401 Unauthorized (Bearer)

Check OPIK_API_KEY. For self-hosted, also set --apiUrl http://host:5173/api.

Verificar: curl -H 'Authorization: Bearer $KEY' $URL/api/v1/workspaces
Empty trace list despite traffic

Wrong project / workspace. List projects first and confirm UUID.

Self-hosted MCP can't reach backend

Use container networking (same docker network) or map --apiUrl to an externally-reachable URL.

Alternativas

opik-mcp vs otros

AlternativaCuándo usarlaContrapartida
LangSmith MCPYou use LangSmith for tracingDifferent platform; similar capabilities
Langfuse MCPYou use Langfuse (OSS)Also OSS + self-hostable; different schemas
Arize / PhoenixYou want focus on evals + drift detectionRicher ML-monitoring features; steeper learning curve

Más

Recursos

📖 Lee el README oficial en GitHub

🐙 Ver issues abiertas

🔍 Ver todos los 400+ servidores MCP y Skills