Calibration Explorer
Check classifier confidence against accuracy, fit temperature scaling and save local reports.
Servidor MCP · de m-sanchez
Resumo
Calibration Explorer é um servidor MCP publicado por m-sanchez. Marketplaces que lemos e que o listam: 2 (Official MCP Registry, Community GitHub marketplaces). Vimos pela primeira vez em 2026-10-11 e não registramos mudanças desde então. Conforme nossa passagem pelos marketplaces em 2026-10-14.
O que pede
- Roda na sua máquina
Nenhum dos marketplaces que lemos publica as ferramentas ou as configurações que ele pede.
Exige: --input-root, --output-root
O que declara, pede e executa, por completo
Instale apenas plugins de desenvolvedores em quem você confia. Mostramos o que os marketplaces publicam e não testamos plugins.
Pacote
npm @m-sanchez/calibration-explorer-mcp (@m-sanchez/calibration-explorer-mcp no npm)
- Downloads do npm por semana: 259 (2026-10-12)
- Downloads do npm por mês: 259 (2026-10-12)
- Última versão no npm: 0.2.0, publicada em 2026-10-05
- A versão declarada 0.2.0 não consta no npm
Os dados do npm vêm do registro público do npm (registry.npmjs.org, api.npmjs.org). Cada número é do próprio registro e nunca é somado a outro. Um registro que não publica um número não mostra nenhum: sem número não é zero.
Funciona com
- Claude Code
- Codex
- Cursor
- VS Code
- Copilot CLI
Um link de um clique abre o cliente, que pede confirmação antes de adicionar o servidor.
Pelos marketplaces que o listam e pelo transporte MCP que declara, conforme cada cliente documenta. Não testamos plugins.
Conectar
Comandos e configurações gerados apenas a partir do que os marketplaces declaram. Não os executamos por você e não testamos plugins.
Como servidor MCP local: pacote npm
Gerado a partir do que Official MCP Registry declara.
claude mcp add --transport stdio calibration-explorer -- npx -y @m-sanchez/calibration-explorer-mcp --input-root "<YOUR_INPUT_ROOT>" --output-root "<YOUR_OUTPUT_ROOT>"
[mcp_servers.calibration-explorer]
command = "npx"
args = ["-y", "@m-sanchez/calibration-explorer-mcp", "--input-root", "<YOUR_INPUT_ROOT>", "--output-root", "<YOUR_OUTPUT_ROOT>"]
{
"mcpServers": {
"calibration-explorer": {
"command": "npx",
"args": [
"-y",
"@m-sanchez/calibration-explorer-mcp",
"--input-root",
"<YOUR_INPUT_ROOT>",
"--output-root",
"<YOUR_OUTPUT_ROOT>"
]
}
}
}
Substitua os valores entre sinais de menor e maior pelos seus. Mostramos os nomes das configurações, nunca valores.
Como plugin do Claude Code
Gerado a partir do que Community GitHub marketplaces declara.
/plugin marketplace add m-sanchez/calibration-explorer
/plugin install calibration-explorer@calibration-explorer
Onde está publicado
| Marketplace | Status | Versão | Números | Verificado | Visto pela primeira vez |
|---|---|---|---|---|---|
| Official MCP Registry (Abrir o registro) | Listado | 0.2.0 | Downloads por mês (npm): 259 Downloads por semana (npm): 259 Forks (GitHub): 0 Estrelas (GitHub): 0 |
Sem marcação |
Cada número é do próprio marketplace e nunca é somado entre marketplaces. Um marketplace que não publica números não mostra nenhum: sem número não é zero.
Também listado em um marketplace da comunidade
| Marketplace | Repositório | Estrelas (GitHub) |
|---|---|---|
| calibration-explorer | m-sanchez/calibration-explorer | 0 |
O que o pacote contém
Conforme publicado em Community GitHub marketplaces.
Servidores MCP: 1
calibration
O que mudou
- Apareceu em um novo marketplace: Community GitHub marketplaces
- Community GitHub marketplaces: apareceu
Plugins semelhantes
Produtos cujos próprios nomes, descrições, ferramentas e skills são os mais próximos deste pelo significado, em todos os marketplaces que lemos. A proximidade é ordenada apenas dentro desta lista.
-
Build datasets and rubrics, then run evals that score your AI in Caliper.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
-
Mini Data Engine Runtime Copilot
MCP runtime copilot for health checks, regressions, explainability, and operational memory.
-
Audit an MCP config, price a model, size a GPU, explain network config drift. Key-free.
-
SomaCheck returns proposition-specific Aligned or Unaligned plus model confidence.
-
Use your own trained text and picture classification models from any AI assistant.
-
explainability-report-mcp io.github.CSOAI-ORG/explainability-report-mcp
Explainability Report MCP Server by MEOK AI Labs
-
Give your AI a research team. Forecast, score, classify, or research every row of a dataset.
-
Read, measure and explain LLM eval runs of a digline suite. Cannot promote a baseline.
Plugins semelhantes por marketplace
A mesma pergunta feita a cada marketplace separadamente: existe lá um equivalente deste plugin?
Listado em Claude Code: claude-plugins-community (5)
-
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…
-
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…
-
Claude model selection advisor — recommends optimal model for each task via shell hook. Zero attack surface.
-
End-to-end data analysis workflow plugin for Claude Code. Covers the full pipeline from EDA to model training - EDA, preprocessing, statistical analysis, feature engineering, and…
-
AI agent evaluation sandbox for Claude Code. Holdout scenario testing with Doer/Judge/Adversary/Observer roles, probabilistic satisfaction scoring, and append-only JSONL audit…
Listado em 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 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…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Find the right NVIDIA skill for GPU acceleration, CUDA, AI agents, data loading, training, inference, robotics, Physical AI, Omniverse, simulation, and other NVIDIA-powered…
Listado em Claude: knowledge-work-plugins (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
-
Hosted MCP server for AI-assisted Grafana Cloud observability — no local installation required.
-
A suite of agent skills for the full GrowthBook feature flag and experimentation lifecycle.
-
Build multimodal AI applications with Pixeltable -- tables, computed columns, embedding search, UDFs, tool-calling agents, and 25+ AI provider integrations.
Listado em Codex: openai-curated (openai/plugins) (5)
-
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces…
-
Evaluate Codex skills and plugins from chat with a beginner-friendly start command, local-first reports, token budget explanations, and guided benchmarking.
-
Predict structures, screen molecules and proteins, and design binders.
-
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…
Listado em Community GitHub marketplaces (5)
-
Exactly explainable classifiers for agents: train, tune, predict, explain on CSV or Excel.
-
Tuning Engines - Governed AI Runtime
Govern model, agent, skill, and MCP workflows with policy, approvals, traces, and usage analytics.
-
codabench-mcp io.github.harshitAgr/codabench-mcp
MCP server for the Codabench REST API — drives a full ML-benchmark participant workflow.
-
Skills for adding DeepEval evaluations, tracing, datasets, Confident AI reports, and iterative improvement loops to AI applications.
-
Finds what shipped after your coding agent's training, before it rebuilds it from scratch.
Listado em Copilot CLI: github/awesome-copilot (5)
-
Safe BLE diagnostics, evidence workflows, and guarded automation for AI agents.
-
Visualizes live session AI-credit usage as a Pac-Man board with pellets, ghosts, fruit milestones, and game-over limits.
-
Run a lightweight, role-separated AI development team with flexible tools, developer-selected models, proportionate planning, and optional QA.
-
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.
Listado em Copilot CLI: github/copilot-plugins (5)
-
Toolkit for building Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, and capability configuration.
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
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…
-
mcp-apps
Generate MCP App widgets for MCP tools. Produces self-contained HTML widgets using the MCP Apps protocol.
-
Analyze MSVC build performance using vcperf.exe and ETL traces.
Listado em Cursor: cursor/plugins (5)
-
Inspect and manage feature gates, experiments, dynamic configs, and metrics.
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
-
CLI-backed repo compatibility scans plus agents that audit startup, validation, and docs against reality.
-
Iterative self-referential AI loops using the Ralph Wiggum technique.
-
playwright-mcp io.github.microsoft/playwright-mcp
Playwright Tools for MCP
Listado em Docker MCP Catalog (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
MCP server for Polar Signals Cloud continuous profiling platform, enabling AI assistants to analyze CPU performance, memory usage, and identify optimization opportunities in…
-
Seamless interaction with Novita AI platform resources.
-
MCP server providing Prometheus metrics access and PromQL query execution for AI assistants
-
testkube-mcp io.github.kubeshop/testkube-mcp
MCP server for Testkube - Manage test workflows, executions, and artifacts via AI assistants
Listado em Official MCP Registry (5)
-
Build datasets and rubrics, then run evals that score your AI in Caliper.
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
-
Mini Data Engine Runtime Copilot
MCP runtime copilot for health checks, regressions, explainability, and operational memory.
-
Audit an MCP config, price a model, size a GPU, explain network config drift. Key-free.
Encontrados pelo significado, não por código ou repositório em comum: plugins semelhantes continuam sendo produtos distintos, e isto não é uma avaliação nem uma recomendação.
Este plugin é seu?
Adicione-o aos seus projetos e prove que o mantém com um arquivo no repositório, um arquivo no seu domínio ou um registro DNS. Você recebe alertas quando um marketplace o publica, o remove, muda a marca de verificado ou o que ele pede, e o endpoint remoto passa a ser monitorado como um serviço web.
Dados de Official MCP Registry. Dados de Community GitHub marketplaces. Os números vêm das nossas próprias passagens regulares pelos marketplaces, última leitura em . Não publicamos dados de contato dos editores de plugins.