io.github.us-all/mlflow
MLflow MCP — experiments, runs, registered models, versions, traces, assessments (MLflow 3)
MCP server · by us-all
About
io.github.us-all/mlflow is an MCP server published by us-all. Marketplaces we read that list it: 1 (Official MCP Registry). We first saw it on 2026-10-11 and have recorded no change since. As of our marketplace pass on 2026-10-12.
What it asks for
- Runs on your machine
- Secrets: 2
- Settings: 8
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.
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 local MCP server: npm package
Built from what Official MCP Registry declares.
claude mcp add --env "MLFLOW_TRACKING_PASSWORD=<YOUR_MLFLOW_TRACKING_PASSWORD>" --env "MLFLOW_TRACKING_TOKEN=<YOUR_MLFLOW_TRACKING_TOKEN>" --env "MLFLOW_TRACKING_URI=<YOUR_MLFLOW_TRACKING_URI>" --transport stdio mlflow -- npx -y @us-all/mlflow-mcp[mcp_servers.mlflow]
command = "npx"
args = ["-y", "@us-all/mlflow-mcp"]
[mcp_servers.mlflow.env]
MLFLOW_TRACKING_PASSWORD = "<YOUR_MLFLOW_TRACKING_PASSWORD>"
MLFLOW_TRACKING_TOKEN = "<YOUR_MLFLOW_TRACKING_TOKEN>"
MLFLOW_TRACKING_URI = "<YOUR_MLFLOW_TRACKING_URI>"{
"mcpServers": {
"mlflow": {
"command": "npx",
"args": [
"-y",
"@us-all/mlflow-mcp"
],
"env": {
"MLFLOW_TRACKING_PASSWORD": "<YOUR_MLFLOW_TRACKING_PASSWORD>",
"MLFLOW_TRACKING_TOKEN": "<YOUR_MLFLOW_TRACKING_TOKEN>",
"MLFLOW_TRACKING_URI": "<YOUR_MLFLOW_TRACKING_URI>"
}
}
}
}Replace the values in angle brackets with your own. We show the names of the settings, never values.
Optional settings it also lists: MLFLOW_ALLOW_WRITE, MLFLOW_DISABLE, MLFLOW_EXPERIMENT_ID, MLFLOW_TOOLS, MLFLOW_TRACKING_USERNAME.
We do not store launch arguments. If the server needs any, its own documentation names them.
Where it is published
| Marketplace | Status | Version | Figures | Verified | First seen |
|---|---|---|---|---|---|
| Official MCP Registry (Open the registry record) | Listed | 1.12.7 | Forks (GitHub): 0 Stars (GitHub): 1 |
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.
-
Skills for tracing, evaluating, and improving AI agents with MLflow. Supports the full agent improvement loop: instrument → trace → evaluate → iterate → validate.
-
weightsbiases-mcp io.github.mrfentmen/weightsbiases-mcp
MCP server for Weights & Biases: profile, projects, runs. Needs a free API key.
-
pramana-mcp io.github.loopg/pramana-mcp
Read your recorded AI agent runs, and what changed when you swapped a model or prompt.
-
okahu co.okahu.mcp-registry/okahu
Cloud hosted Okahu MCP server that helps you manage genAI trace data
-
Train, track and query models on a running dashAI instance. Read-oriented, no delete tools.
-
Manage your Mistral platform — models, files, batch jobs, agents and RAG document libraries.
-
replicate com.mcparmory/replicate
Run AI models, create deployments, and manage predictions via cloud API
-
Hugging Face Hub MCP — models, datasets, spaces
-
Run fal.ai models, poll the inference queue and read model schemas.
-
MCP server for Ultralytics Platform projects, datasets, training, prediction, exports, and models.
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)
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
-
agent-tasks io.github.keshrath/agent-tasks
Pipeline task management for AI agents - stages, dependencies, artifacts, claiming
-
DataRobot Agent Skills - Agentic skills for DataRobot enterprise AI and ML workflows. Covers model training, deployment, predictions, feature engineering, monitoring…
-
agent-discover io.github.keshrath/agent-discover
Find, install and enable MCP servers mid-session on any host, with consent and tool pinning
-
Build, run, and monitor AI/ML workflows on Jetty — from prompt to production in 5 minutes.
Has a listing on Claude Code: claude-plugins-official (5)
-
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…
-
Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams
-
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.
-
Skills for working with Langfuse, the open-source LLM engineering platform for tracing, prompt management, and evaluation.
Has a listing on 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.
-
Official SigNoz plugin for MCP setup, docs, queries, dashboards, and alerts
-
Use Datadog directly in Claude Code through a preconfigured Datadog MCP server. Query logs, metrics, traces, dashboards, and more through natural conversation. This plugin is in…
Has a listing on 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…
-
Comprehensive skill for the entire Temporal lifecycle — developing applications, using the Temporal CLI, running and managing Temporal Server, and working with Temporal Cloud.
-
Build with OpenAI APIs, Agents SDK, and ChatGPT Apps, and create and save OpenAI API keys from Codex.
-
CrowdStrike Falcon Foundry development skills for building cybersecurity applications on the Falcon platform. Includes UI development, collections, functions, workflows, API…
-
Available for US1 customers only. Analyze, investigate, and act on your Datadog telemetry directly from ChatGPT using natural language. Ask questions about your production…
Has a listing on Community GitHub marketplaces (5)
-
DataRobot skills for AI/ML workflows — model training, deployment, predictions, feature engineering, monitoring, explainability, data preparation, App Framework CI/CD, and…
-
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.
-
Databricks skills for the CLI, Apps, Lakebase, Model Serving, Lakeflow Jobs, Spark Declarative Pipelines, Declarative Automation Bundles (DABs), and classic-to-serverless…
-
Dynatrace observability skills: DQL query patterns, application and infrastructure monitoring, log analysis, problem investigation, and incident response workflows, with the…
-
Dash0 Observability
OpenTelemetry observability for OpenAI Codex sessions. Captures prompts, tool calls, MCP calls, sub-agent activity, and token usage as OTel traces.
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.
-
Complete toolkit for building Model Context Protocol (MCP) servers in Go using the official github.com/modelcontextprotocol/go-sdk. Includes instructions for best practices, a…
-
Use Datadog directly in Copilot / VS Code through a preconfigured Datadog MCP server. Query logs, metrics, traces, dashboards, and more through natural conversation.
-
Interactive GitHub Copilot canvas for discovering, connecting, and managing hosted MCP servers from an Azure Connector Namespace.
-
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.
-
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…
-
Build Power Apps Canvas Apps using the Canvas Authoring MCP server.
-
mcp-apps
Generate MCP App widgets for MCP tools. Produces self-contained HTML widgets using the MCP Apps protocol.
-
Complete bundle: all Microsoft Skills for Fabric for developers and consumers.
Has a listing on Cursor: cursor/plugins (5)
-
Fan large tasks out across parallel cloud agents with planners, workers, verifiers, and structured handoffs.
-
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…
-
Build apps, scripts, and automations with the TypeScript SDK.
-
Explore datasets and tables and run SQL queries.
Has a listing on Docker MCP Catalog (5)
-
Read and score Opik traces, experiments, datasets and prompts from your AI assistant.
-
testkube-mcp io.github.kubeshop/testkube-mcp
MCP server for Testkube - Manage test workflows, executions, and artifacts via AI assistants
-
MCP server providing Prometheus metrics access and PromQL query execution for AI assistants
-
Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.
-
A universal MCP (Model Context Protocol) server to integrate any API with Claude Desktop using only Docker configurations.
Has a listing on Official MCP Registry (5)
-
weightsbiases-mcp io.github.mrfentmen/weightsbiases-mcp
MCP server for Weights & Biases: profile, projects, runs. Needs a free API key.
-
pramana-mcp io.github.loopg/pramana-mcp
Read your recorded AI agent runs, and what changed when you swapped a model or prompt.
-
okahu co.okahu.mcp-registry/okahu
Cloud hosted Okahu MCP server that helps you manage genAI trace data
-
Train, track and query models on a running dashAI instance. Read-oriented, no delete tools.
-
Manage your Mistral platform — models, files, batch jobs, agents and RAG document libraries.
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?
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 can put its remote endpoint on monitoring as a web service.
Data comes from the Official MCP Registry (registry.modelcontextprotocol.io), CC0 1.0. Figures come from our own regular passes over the marketplaces, last read on . We publish no contact details for plugin publishers.