Todoist MCP Server for LlamaIndex 7 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Todoist as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Todoist. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Todoist?"
)
print(response)
asyncio.run(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 Todoist MCP Server
Connect your Todoist account to any AI agent and bring your daily productivity directly into your chat. View your active tasks, manage projects, and quickly add new items to your workflow entirely through conversational commands without ever needing to open the app.
LlamaIndex agents combine Todoist tool responses with indexed documents for comprehensive, grounded answers. Connect 7 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Project Management — List all your active project folders, retrieve their specific IDs, and view sections within specific projects
- Task Execution — View your complete list of pending tasks and mark them as completed instantly
- Create Tasks — Add new items to a specific project or your inbox naturally in plain conversation
- Organization — Look up available labels/tags to categorize your work
- Collaboration — Read through existing comments to catch up on discussion history for any particular task
The Todoist MCP Server exposes 7 tools through the Vinkius. Connect it to LlamaIndex 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 Todoist to LlamaIndex via MCP
Follow these steps to integrate the Todoist MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 7 tools from Todoist
Why Use LlamaIndex with the Todoist MCP Server
LlamaIndex provides unique advantages when paired with Todoist through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Todoist tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Todoist tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Todoist, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Todoist tools were called, what data was returned, and how it influenced the final answer
Todoist + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Todoist MCP Server delivers measurable value.
Hybrid search: combine Todoist real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Todoist to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Todoist for fresh data
Analytical workflows: chain Todoist queries with LlamaIndex's data connectors to build multi-source analytical reports
Todoist MCP Tools for LlamaIndex (7)
These 7 tools become available when you connect Todoist to LlamaIndex via MCP:
complete_task
Marks a task as completed
create_task
Provide content and an optional project ID. Creates a new task in Todoist
list_comments
Lists all comments for a specific task
list_labels
Lists all user-defined labels
list_projects
Lists all active projects in Todoist
list_sections
Lists all sections within a specific project
list_tasks
Can filter by project_id. Lists active tasks, optionally filtered by project
Example Prompts for Todoist in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Todoist immediately.
"Check all my active tasks and projects."
"Complete the task with ID 81229."
Troubleshooting Todoist MCP Server with LlamaIndex
Common issues when connecting Todoist to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTodoist + LlamaIndex FAQ
Common questions about integrating Todoist MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Todoist 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 Todoist to LlamaIndex
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.