Why can't the agent read my task names?

Lunatask uses end-to-end encryption. Task names and note bodies are encrypted on your device before being sent to the server. The API only has access to metadata like IDs and statuses.

Where do I find my Area ID?

In the Lunatask desktop app, go to an Area's settings. The unique Area ID (UUID) is displayed there for use in the API.

Can I track habits using this agent?

Yes, use the `track_habit_completion` tool with the unique habit ID to log a successful completion event.

Lunatask MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Lunatask
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Lunatask through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "lunatask": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Lunatask, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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 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.

LangChain's ecosystem of 500+ components combines seamlessly with Lunatask through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Lunatask MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Lunatask via MCP

Why Use LangChain with the Lunatask MCP Server

LangChain provides unique advantages when paired with Lunatask through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Lunatask MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Lunatask queries for multi-turn workflows

Lunatask + LangChain Use Cases

Practical scenarios where LangChain combined with the Lunatask MCP Server delivers measurable value.

RAG with live data: combine Lunatask tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Lunatask, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Lunatask tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Lunatask tool call, measure latency, and optimize your agent's performance

Lunatask MCP Tools for LangChain (8)

These 8 tools become available when you connect Lunatask to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting Lunatask to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Lunatask + LangChain FAQ

Common questions about integrating Lunatask MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.