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Vinkius

Portkey MCP Server for Mastra AI 10 tools — connect in under 2 minutes

Built by Vinkius GDPR 10 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Portkey through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.

Vinkius supports streamable HTTP and SSE.

typescript
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: {
      "portkey": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Portkey Agent",
    instructions:
      "You help users interact with Portkey " +
      "using 10 tools.",
    model: openai("gpt-4o"),
    tools,
  });

  const result = await agent.generate(
    "What can I do with Portkey?"
  );
  console.log(result.text);
}

main();
Portkey
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Portkey MCP Server

What you can do

Connect AI agents to the Portkey AI Gateway for enterprise-grade observability and management:

Mastra's agent abstraction provides a clean separation between LLM logic and Portkey tool infrastructure. Connect 10 tools through the 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.

  • Monitor logs and traces of all LLM calls passing through your gateway
  • Analyze token usage, latency, and costs across models and teams
  • Submit feedback (Likes/Dislikes) to improve model quality and agent performance
  • Export logs for audit trails, compliance, and offline cost analysis
  • Review gateway configurations including retry policies, fallbacks, and cache settings
  • Manage virtual keys to track provider API key usage and limits
  • Discover supported models from 1,600+ LLMs available via Portkey
  • Enforce budget policies to prevent runaway AI costs per team or project

The Portkey 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 Portkey to Mastra AI via MCP

Follow these steps to integrate the Portkey MCP Server with Mastra AI.

01

Install dependencies

Run npm install @mastra/core @mastra/mcp @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

Mastra discovers 10 tools from Portkey via MCP

Why Use Mastra AI with the Portkey MCP Server

Mastra AI provides unique advantages when paired with Portkey through the Model Context Protocol.

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Portkey without touching business code

02

Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation

03

TypeScript-native: full type inference for every Portkey tool response with IDE autocomplete and compile-time checks

04

One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure

Portkey + Mastra AI Use Cases

Practical scenarios where Mastra AI combined with the Portkey MCP Server delivers measurable value.

01

Automated workflows: build multi-step agents that query Portkey, process results, and trigger downstream actions in a typed pipeline

02

SaaS integrations: embed Portkey as a first-class tool in your product's AI features with Mastra's clean agent API

03

Background jobs: schedule Mastra agents to query Portkey on a cron and store results in your database automatically

04

Multi-agent systems: create specialist agents that collaborate using Portkey tools alongside other MCP servers

Portkey MCP Tools for Mastra AI (10)

These 10 tools become available when you connect Portkey to Mastra AI via MCP:

01

create_policy

Requires policy name, budget limit (USD or token count), and optionally the target users or virtual keys to restrict. Returns the created policy details. Use this to enforce cost controls on specific teams or projects using the gateway. Create a new budget or usage policy for AI gateway access

02

delete_policy

Requires the policy ID. Use this when a project ends or budget constraints are no longer needed. Remove a budget or usage policy from Portkey

03

export_logs

Optionally filters by date range, model, or user. Returns an export ID or download URL. Use this for audit trails, cost reporting, or offline analysis of AI usage patterns. Export AI gateway logs for external analysis or compliance reporting

04

get_log_details

Requires the log ID from list_logs results. Use this for deep debugging of specific AI interactions. Get detailed information about a specific AI gateway log entry

05

get_virtual_keys

Virtual keys map to underlying provider keys (OpenAI, Anthropic, etc.) with metadata, usage limits, and policy associations. Returns key IDs, names, provider targets, current usage, and status. Use this to audit API key usage or identify keys approaching limits. List all virtual API keys managed by Portkey

06

list_configs

Returns config IDs, names, creation dates, and associated virtual keys. Use this to review how LLM requests are routed or to audit gateway behavior. List all gateway configurations stored in Portkey

07

list_logs

Returns log IDs, timestamps, model names, token usage, latency, costs, and status codes. Use this to monitor AI usage, identify expensive calls, or debug latency issues. Supports pagination via limit/offset. List recent AI gateway logs and traces from Portkey

08

list_models

). Returns model names, provider names, supported endpoints (chat, embeddings, etc.), and capabilities. Use this to discover which models are routable via your gateway. List all LLM models supported by the Portkey gateway

09

list_policies

Returns policy names, limits, current consumption, and affected users/keys. Use this to review guardrails preventing runaway AI costs. List all budget and usage policies defined in Portkey

10

submit_feedback

Requires the log ID, rating (LIKE, DISLIKE, or UNLIKE to remove), and optional text feedback. Use this to build RLHF datasets or monitor user satisfaction with AI outputs. Submit user feedback (Like/Dislike) for a specific AI response log

Example Prompts for Portkey in Mastra AI

Ready-to-use prompts you can give your Mastra AI agent to start working with Portkey immediately.

01

"Show me the most expensive LLM calls from the last 24 hours"

02

"Create a budget policy limiting the Marketing team to $500/month on LLM usage"

03

"Export all logs from last week for our compliance audit"

Troubleshooting Portkey MCP Server with Mastra AI

Common issues when connecting Portkey to Mastra AI through the Vinkius, and how to resolve them.

01

createMCPClient not exported

Install: npm install @mastra/mcp

Portkey + Mastra AI FAQ

Common questions about integrating Portkey MCP Server with Mastra AI.

01

How does Mastra AI connect to MCP servers?

Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
02

Can Mastra agents use tools from multiple servers?

Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
03

Does Mastra support workflow orchestration?

Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.

Connect Portkey to Mastra AI

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.