Helicone (LLM Observability) MCP Server for Mastra AI 10 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Helicone (LLM Observability) 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: {
"helicone-llm-observability": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Helicone (LLM Observability) Agent",
instructions:
"You help users interact with Helicone (LLM Observability) " +
"using 10 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Helicone (LLM Observability)?"
);
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 Helicone (LLM Observability) MCP Server
Connect your Helicone account to any AI agent and take full control of your LLM observability and gateway monitoring through natural conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and Helicone (LLM Observability) tool infrastructure. Connect 10 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
- Request Monitoring — Query deep proxy logs to inspect exact prompts and outputs sent to LLM APIs directly from your agent
- Cost Analysis — Break down spending by model, user, or custom metadata properties to monitor your AI burn rate in real-time
- Latency Optimization — Measure Time To First Token (TTFT) and pinpoint slowness caused by specific upstream LLM providers
- Prompt Management — Access managed prompt versions and track iterative changes in your AI instruction logic natively
- Session Tracing — Isolate and analyze multi-turn graph traces connecting consecutive LLM calls to debug complex agentic workflows
- User Insights — Track precise LLM interactions based on Helicone tags and identify your most active human clients
- Feedback & RLHF — Extract user critiques (Thumbs Up/Down) and log offline Human-in-the-Loop verdicts to improve model grounding
The Helicone (LLM Observability) MCP Server exposes 10 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 Helicone (LLM Observability) to Mastra AI via MCP
Follow these steps to integrate the Helicone (LLM Observability) 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 10 tools from Helicone (LLM Observability) via MCP
Why Use Mastra AI with the Helicone (LLM Observability) MCP Server
Mastra AI provides unique advantages when paired with Helicone (LLM Observability) through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Helicone (LLM Observability) 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 Helicone (LLM Observability) 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
Helicone (LLM Observability) + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Helicone (LLM Observability) MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Helicone (LLM Observability), process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Helicone (LLM Observability) as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Helicone (LLM Observability) on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Helicone (LLM Observability) tools alongside other MCP servers
Helicone (LLM Observability) MCP Tools for Mastra AI (10)
These 10 tools become available when you connect Helicone (LLM Observability) to Mastra AI via MCP:
get_prompt_versions
Irreversibly vaporize explicit validations extracting rich Churn flags
list_properties
Identify precise active arrays spanning native Gateway auth
log_feedback
Identify precise active arrays spanning native Hold parsing
query_costs
Perform structural extraction of properties driving active Account logic
query_feedback
Inspect deep internal arrays mitigating specific Plan Math
query_latency
Provision a highly-available JSON Payload generating hard Customer bindings
query_prompts
Retrieve explicit Cloud logging tracing explicit Vault limits
query_requests
Identify bounded CRM records inside the Headless Helicone Platform
query_sessions
Enumerate explicitly attached structured rules exporting active Billing
query_users
Dispatch an automated validation check routing explicit Gateway history
Example Prompts for Helicone (LLM Observability) in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Helicone (LLM Observability) immediately.
"How much did we spend on GPT-4o yesterday?"
"Show me the 10 slowest requests from the last hour"
"List all versions for the 'customer-service-bot' prompt"
Troubleshooting Helicone (LLM Observability) MCP Server with Mastra AI
Common issues when connecting Helicone (LLM Observability) to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpHelicone (LLM Observability) + Mastra AI FAQ
Common questions about integrating Helicone (LLM Observability) 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 Helicone (LLM Observability) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
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 Helicone (LLM Observability) to Mastra AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.