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Vinkius

Runlayer MCP Server for Mastra AI 27 tools — connect in under 2 minutes

Built by Vinkius GDPR 27 Tools SDK

Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Runlayer 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: {
      "runlayer": {
        url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
      },
    },
  });

  const tools = await mcpClient.getTools();
  const agent = new Agent({
    name: "Runlayer Agent",
    instructions:
      "You help users interact with Runlayer " +
      "using 27 tools.",
    model: openai("gpt-4o"),
    tools,
  });

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

main();
Runlayer
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 Runlayer MCP Server

What you can do

Connect AI agents to the Runlayer Enterprise Control Plane for comprehensive MCP ecosystem management:

Mastra's agent abstraction provides a clean separation between LLM logic and Runlayer tool infrastructure. Connect 27 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.

  • Manage MCP Servers — register, inspect, update, and remove serverless MCP endpoints
  • Manage Skills — create, assign, and version reusable agent capabilities
  • Manage Agents — onboard AI agents (Claude, Cursor, VS Code, custom) with proper security guardrails
  • Enforce Policies — define and audit security policies governing MCP access and agent permissions
  • Audit Everything — retrieve complete audit trails of all MCP, skill, agent, and policy operations
  • Manage API Keys — create, rotate, and revoke organization and personal API keys
  • Run Security Scans — discover shadow AI, unauthorized MCP servers, and policy violations across your organization
  • Monitor Organization Health — review member activity, server inventory, and security posture

The Runlayer MCP Server exposes 27 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 Runlayer to Mastra AI via MCP

Follow these steps to integrate the Runlayer 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 27 tools from Runlayer via MCP

Why Use Mastra AI with the Runlayer MCP Server

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

01

Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Runlayer 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 Runlayer 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

Runlayer + Mastra AI Use Cases

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

01

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

02

SaaS integrations: embed Runlayer 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 Runlayer on a cron and store results in your database automatically

04

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

Runlayer MCP Tools for Mastra AI (27)

These 27 tools become available when you connect Runlayer to Mastra AI via MCP:

01

create_agent

Requires agent name and type (claude_desktop, cursor, vs_code, custom). Optionally assign MCP servers, skills, and policies during registration. Returns the created agent details. Use this to onboard new AI agents to your enterprise control plane with proper security guardrails. Register a new AI agent in Runlayer

02

create_api_key

Returns the key value (shown only once) and metadata. Use this to create keys for integrations, CI/CD pipelines, or service accounts. Store the key value securely immediately after creation. Create a new API key for your Runlayer organization

03

create_mcp_server

Requires server name and connection details (URL, authentication method). Optionally assign skills, agents, and policies during registration. Returns the created server details including the new UUID. Use this to onboard new MCP servers to your enterprise control plane. Register a new MCP server in Runlayer

04

create_policy

Requires policy name and rule definitions. Returns the created policy. Use this to enforce security standards, restrict access to sensitive MCP servers, or define audit requirements. Create a new security or access policy in Runlayer

05

create_skill

Requires skill name and description. Optionally define input/output schemas and initial MCP server assignments. Returns the created skill details. Use this to codify reusable agent capabilities for consistent use across your organization. Register a new skill (agent capability) in Runlayer

06

delete_agent

This disconnects the agent from all MCP servers and removes policy assignments. Requires the agent ID. Confirm with the user before proceeding. Remove an AI agent from Runlayer

07

delete_mcp_server

This action disconnects all associated agents and removes policy assignments. Requires the server UUID. Confirm with the user before proceeding. Remove an MCP server from Runlayer

08

delete_policy

All resources previously governed by this policy will no longer be subject to its rules. Requires the policy ID. Confirm with the user before proceeding. Remove a security or access policy from Runlayer

09

delete_skill

Does not delete the underlying MCP server tools. Requires the skill ID. Confirm with the user before proceeding. Remove a skill from Runlayer

10

get_agent

Requires the agent ID from list_agents results. Use this to review agent configuration, audit access patterns, or troubleshoot connectivity. Get detailed information about a specific AI agent

11

get_audit_logs

Returns timestamps, actor identities, action types, affected resources, and outcomes. Use this for compliance reporting, security investigations, or operational troubleshooting. Get audit logs for your Runlayer organization

12

get_mcp_server

Requires the server UUID from list_mcp_servers results. Use this to review server configuration, verify security compliance, or troubleshoot connectivity issues. Get detailed information about a specific MCP server

13

get_organization

Use this to verify your organization configuration or get an overview of your MCP ecosystem. Get your Runlayer organization details

14

get_scan_results

Requires the scan ID from run_mcp_sweep_scan results. Use this to review shadow AI discoveries, identify policy violations, or generate compliance reports. Get results from an MCP sweep scan

15

get_skill

Requires the skill ID from list_skills results. Use this to review skill configuration or understand capability dependencies. Get detailed information about a specific skill

16

list_agents

Returns agent names, IDs, types (Claude Desktop, Cursor, custom), assigned MCP servers, active skills, policy compliance status, and last activity timestamps. Use this to understand your agent ecosystem and verify which agents have access to which MCP servers. List all AI agents registered in your Runlayer organization

17

list_api_keys

Use this to audit key inventory, identify unused keys, or prepare for key rotation. List all API keys for your Runlayer organization

18

list_mcp_servers

Returns server names, UUIDs, status (active, inactive, blocked), assigned skills, connected agents, policy associations, and last activity timestamps. Use this as the first step to understand your MCP server inventory before managing individual servers, applying policies, or reviewing security posture. List all registered MCP servers in your Runlayer organization

19

list_members

Use this to audit access, review role assignments, or identify inactive accounts. List all members of your Runlayer organization

20

list_policies

Returns policy names, descriptions, enforcement status, affected resources, and violation counts. Use this to review your security posture before creating or modifying policies. List all security and access policies in your Runlayer organization

21

list_skills

Returns skill names, descriptions, associated MCP servers, usage counts, and version information. Use this to discover available capabilities before assigning them to agents or MCP servers. List all skills registered in your Runlayer organization

22

revoke_api_key

This action cannot be undone. Requires the key ID. Use this for compromised keys, unused keys, or during security incidents. Revoke an API key immediately

23

run_mcp_sweep_scan

Returns a scan ID which can be used with get_scan_results to retrieve findings. Use this for security assessments, compliance audits, or shadow AI detection. Run an MCP sweep scan to discover shadow AI across your organization

24

update_agent

Only pass the fields you want to change. Requires the agent ID. Use this to update agent assignments or modify metadata. Update an existing AI agent configuration

25

update_mcp_server

Only pass the fields you want to change. Requires the server UUID. Use this to update server endpoints, rotate credentials, or modify policy assignments. Update an existing MCP server configuration

26

update_policy

Only pass the fields you want to change. Requires the policy ID. Use this to refine security requirements, update access controls, or modify audit rules. Update an existing security or access policy

27

update_skill

Only pass the fields you want to change. Requires the skill ID. Use this to refine skill definitions or update documentation. Update an existing skill configuration

Example Prompts for Runlayer in Mastra AI

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

01

"Show me all MCP servers registered in our organization and their security status"

02

"Run a shadow AI discovery scan across our organization and show me the findings"

03

"Create a new policy that restricts MCP server access to only approved developers"

Troubleshooting Runlayer MCP Server with Mastra AI

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

01

createMCPClient not exported

Install: npm install @mastra/mcp

Runlayer + Mastra AI FAQ

Common questions about integrating Runlayer 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 Runlayer to Mastra AI

Get your token, paste the configuration, and start using 27 tools in under 2 minutes. No API key management needed.