Lunatask MCP Server for Mastra AI 8 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Lunatask 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: {
"lunatask": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Lunatask Agent",
instructions:
"You help users interact with Lunatask " +
"using 8 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Lunatask?"
);
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 Lunatask MCP Server
Connect your Lunatask account to any AI agent to streamline your privacy-focused productivity. This MCP server enables your agent to create, update, and manage tasks, track habits, and log journal entries directly from natural language interfaces.
Mastra's agent abstraction provides a clean separation between LLM logic and Lunatask tool infrastructure. Connect 8 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
- Task Creation — Add new tasks to specific Areas of Life with statuses like 'next' or 'later'
- Habit Tracking — Log completions for your daily habits to stay consistent with your goals
- Encrypted Journaling — Create secure, end-to-end encrypted journal entries directly from your conversation
- Metadata Inspection — List all tasks and notes to monitor your productivity structure and statuses
- Workflow Management — Update task priorities and move them through your personal workflow stages
Important Note on Privacy
Lunatask uses end-to-end encryption. While this API allows creating and updating content, it cannot read back the names or notes of your tasks once they are stored. The agent will only see technical metadata (IDs, dates, statuses).
The Lunatask MCP Server exposes 8 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 Lunatask to Mastra AI via MCP
Follow these steps to integrate the Lunatask 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 8 tools from Lunatask via MCP
Why Use Mastra AI with the Lunatask MCP Server
Mastra AI provides unique advantages when paired with Lunatask through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Lunatask 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 Lunatask 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
Lunatask + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Lunatask MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Lunatask, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Lunatask as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Lunatask on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Lunatask tools alongside other MCP servers
Lunatask MCP Tools for Mastra AI (8)
These 8 tools become available when you connect Lunatask to Mastra AI via MCP:
create_journal_entry
Add a new journal entry
create_new_task
Requires a name and an area_id. Create a new task
delete_task
Delete a task
get_task_metadata
Get metadata for a specific task
list_notes_metadata
List metadata for all notes
list_tasks_metadata
Note: Due to encryption, names and notes are not available via API. List metadata for all tasks
track_habit_completion
Log a completion for a habit
update_existing_task
Update an existing task
Example Prompts for Lunatask in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Lunatask immediately.
"List metadata for all my tasks in Lunatask."
"Track a completion for habit ID 'habit-123'."
"Create a new task named 'Review quarterly report' in area 'area-abc'."
Troubleshooting Lunatask MCP Server with Mastra AI
Common issues when connecting Lunatask to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpLunatask + Mastra AI FAQ
Common questions about integrating Lunatask 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 Lunatask 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 Lunatask to Mastra AI
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.