How to Use the Todoist MCP in Pydantic AI

Q: Can I use Todoist to create tasks in Pydantic AI?

Yes. You call createtask, giving it the necessary content and optional project ID. The agent validates this before sending the request.

Q: Does the MCP Server support listing tasks by project for Todoist using Pydantic AI?

You use listtasks and supply a project ID to filter the results. This keeps your list clean and focused on what matters right now.

Q: What if I need to list all available labels for Todoist with Pydantic AI?

You call listlabels. Because of Pydantic's checks, you get a guaranteed clean and correctly structured list of every label.

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Connect Todoist MCP to Pydantic AI

Create your Vinkius account to connect Todoist to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Todoist with Pydantic AI

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Control Tasks via the MCP Server

The MCP Server lets you mark items as finished using `complete_task`. To add new work, simply call `create_task`, passing in content and an optional project ID. The agent validates this data before execution. When running production code, Pydantic AI ensures that the tool calls for Todoist are structured correctly every single time.

Review Todoist Structure with Pydantic AI

You can list all your projects using `list_projects` and then drill down into project organization with `list_sections`. This process ensures the agent knows exactly where everything lives. If you need to see what's currently assigned, `list_tasks` lets you pull a filtered view of active tasks by providing a project ID.

List Todoist Context in Pydantic AI

The agent provides full context on your list. Use `list_labels` to get every tag, or use `list_comments` to see the discussion history for a specific task. This makes sure you never miss background info. This MCP Server guarantees that when your client calls these functions, the input and output data match defined Python models.

Setup guide

Set up Todoist MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "todoist-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Todoist tools.",
)

result = await agent.run("List recent Todoist transactions")
print(result.output)

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Common questions about Todoist MCP in Pydantic AI

Pydantic validates every response from the MCP Server. If the API returns unexpected data, the agent fails loudly with a validation error—you know immediately if something is wrong.

The server touches Tasks, Projects, Labels, Sections, and Comments. All these inputs are validated against Pydantic models for strict type safety.

Yes. You call `create_task`, giving it the necessary content and optional project ID. The agent validates this before sending the request.

You use `list_tasks` and supply a project ID to filter the results. This keeps your list clean and focused on what matters right now.

You call `list_labels`. Because of Pydantic's checks, you get a guaranteed clean and correctly structured list of every label.

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