Todoist MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Complete Task, Create Project, Create Task, and more
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.
Ask AI about this App Connector for LlamaIndex
The Todoist app connector for LlamaIndex is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 12 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 simplify how you organize your life and work through natural conversation.
LlamaIndex agents combine Todoist tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Task Control — Create, update, and complete tasks with full support for due dates, priorities, and descriptions.
- Project Oversight — List all your projects and manage sections to keep your workflows structured.
- Smart Filtering — Query your tasks using Todoist's powerful filter syntax (e.g., 'today', 'p1') via AI.
- Categorization — List and manage labels to tag your tasks across different projects.
- Collaboration — List comments on tasks and projects to track discussions and notes.
- Workspace Maintenance — Reopen completed tasks or fetch detailed metadata for specific to-do items.
The Todoist MCP Server exposes 12 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.
All 12 Todoist tools available for LlamaIndex
When LlamaIndex connects to Todoist through Vinkius, your AI agent gets direct access to every tool listed below — spanning task-management, to-do-list, workflow-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Mark a task as finished
Create a new project
Add a new to-do item
Get metadata for a project
Get details for a specific task
Can filter by project, label, or filter. List active tasks
List your personal labels
List comments for a task or project
List sections within a project
List your Todoist projects
Mark a closed task as active
Modify an existing task
Connect Todoist to LlamaIndex via MCP
Follow these steps to wire Todoist into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
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
Example Prompts for Todoist in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Todoist immediately.
"What are my high priority tasks for today?"
"Create a task in the 'Work' project: 'Submit expense report' due Friday at 5pm."
"Show me all active tasks with the label '@errand'."
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.