Neptune.ai (ML Experiment Tracking) MCP Server for Mastra AI 6 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Neptune.ai (ML Experiment Tracking) through Vinkius and Mastra agents discover all tools automatically. type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token. get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"neptuneai-ml-experiment-tracking": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Neptune.ai (ML Experiment Tracking) Agent",
instructions:
"You help users interact with Neptune.ai (ML Experiment Tracking) " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Neptune.ai (ML Experiment Tracking)?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Neptune.ai (ML Experiment Tracking) MCP Server
Connect your Neptune.ai account to any AI agent and take full control of your machine learning experimentation, model versioning, and training telemetry through natural conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and Neptune.ai (ML Experiment Tracking) tool infrastructure. Connect 6 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
What you can do
- Experiment Orchestration — List all managed ML projects and retrieve detailed metadata configurations tracking active runs and workspace boundaries directly from your agent
- Run Audit & Search — Discover specific training runs or historical experiment state checkpoints mapping deep ML parameter sets and performance bounds securely
- Attribute Inspection — Extract detailed telemetry capturing the exact variables, accuracy metrics, and loss curves logged during specific execution checkpoints natively
- Model Registry Management — List and retrieve trained tracking models promoted and logged explicitly, isolating stable versions from ephemeral experimentation runs
- Organizational Visibility — Enumerate accessible workspaces and projects to understand your ML research footprint and documentation distribution natively
- Credential Audit — Verify specific user identifies and availability details bound inherently against your active service account token securely
- Metadata Retrieval — Deep-dive into specific Project or Run IDs to retrieve precise JSON representations and chronological experimentation insights instantly
The Neptune.ai (ML Experiment Tracking) MCP Server exposes 6 tools through the Vinkius. Connect it to Mastra AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Neptune.ai (ML Experiment Tracking) to Mastra AI via MCP
Follow these steps to integrate the Neptune.ai (ML Experiment Tracking) MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 6 tools from Neptune.ai (ML Experiment Tracking) via MCP
Why Use Mastra AI with the Neptune.ai (ML Experiment Tracking) MCP Server
Mastra AI provides unique advantages when paired with Neptune.ai (ML Experiment Tracking) through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Neptune.ai (ML Experiment Tracking) without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Neptune.ai (ML Experiment Tracking) tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Neptune.ai (ML Experiment Tracking) + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Neptune.ai (ML Experiment Tracking) MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Neptune.ai (ML Experiment Tracking), process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Neptune.ai (ML Experiment Tracking) as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Neptune.ai (ML Experiment Tracking) on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Neptune.ai (ML Experiment Tracking) tools alongside other MCP servers
Neptune.ai (ML Experiment Tracking) MCP Tools for Mastra AI (6)
These 6 tools become available when you connect Neptune.ai (ML Experiment Tracking) to Mastra AI via MCP:
get_attributes
Get parameters mapped within an experiment runtime bounds
get_project
Get specific details for a targeted Neptune ML project
get_user
Get specific user credentials and availability details
list_models
List trained tracking models packaged natively within a project
list_projects
List accessible Neptune workspaces and projects
search_runs
Search explicitly tracked ML experimentation runs inside a project
Example Prompts for Neptune.ai (ML Experiment Tracking) in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Neptune.ai (ML Experiment Tracking) immediately.
"List all training runs for the 'Customer-Churn' project"
"Show me the metrics for run ID 'churn-exp-123'"
"List all registered models in project 'Fraud-Detection'"
Troubleshooting Neptune.ai (ML Experiment Tracking) MCP Server with Mastra AI
Common issues when connecting Neptune.ai (ML Experiment Tracking) to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpNeptune.ai (ML Experiment Tracking) + Mastra AI FAQ
Common questions about integrating Neptune.ai (ML Experiment Tracking) MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
Connect Neptune.ai (ML Experiment Tracking) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Neptune.ai (ML Experiment Tracking) to Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.