Where do I obtain my Toggl Plan Access Token?

Navigate to the Toggl Plan web panel, head over to your **Profile settings**, and locate the Developer/API Integrations segment. You will need a valid Access Token (often labeled API or OAuth Bearer token in your administrative view). Create it permanently and keep the exposed hash secure.

Does the system support permanent deletion of elements?

Yes. This connector features a `delete_timeline_task` handler. If specifically instructed by you, the AI agent is capable of making a permanent removal request which cannot be un-done. You should instruct the AI cautiously when using mutations.

Are there any data sync delays when updating timelines with the agent?

No. Toggl Plan's API ensures immediate reflection of all timeline and milestone changes. When the agent updates a task or resource allocation, it instantly appears in the web interface for all workspace users without any caching delays.

Toggl Plan MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Toggl Plan
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Toggl Plan through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Toggl Plan "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Toggl Plan?"
    )
    print(result.data)

asyncio.run(main())

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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 Toggl Plan MCP Server

Connect your Toggl Plan workspaces to an AI agent entirely bypassing the complex graphical interfaces. Allow your project managers and team leads to directly read, create, and organize workload data, milestones, and daily tasks inside a conversational or command-driven environment.

Pydantic AI validates every Toggl Plan tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Timeline Oversight — Search workspaces to list, read, or inspect the metadata details of specific timeline tasks and milestones
Project Construction — Easily list all the active project segments directly on your terminal to know what your team is facing today
Task Execution — Complete the full cycle of task management: Create new nodes on the timeline, update existing entries, or delete deprecated ones through simple instructions
Fleet Operations — Manage human resources by securely listing all registered workspace users to assign workloads correctly
Taxonomy Organization — Check and retrieve current tagging structures to ensure standardized labels

The Toggl Plan MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic 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 Toggl Plan to Pydantic AI via MCP

Follow these steps to integrate the Toggl Plan MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

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 10 tools from Toggl Plan with type-safe schemas

Why Use Pydantic AI with the Toggl Plan MCP Server

Pydantic AI provides unique advantages when paired with Toggl Plan through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Toggl Plan integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Toggl Plan connection logic from agent behavior for testable, maintainable code

Toggl Plan + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Toggl Plan MCP Server delivers measurable value.

Type-safe data pipelines: query Toggl Plan with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Toggl Plan tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Toggl Plan and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Toggl Plan responses and write comprehensive agent tests

Toggl Plan MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Toggl Plan to Pydantic AI via MCP:

create_timeline_task

Requires workspace ID, task name, and project ID. Creates a new task on the Toggl Plan timeline

delete_timeline_task

This action is irreversible. Permanently deletes a task from the timeline

get_project_details

Retrieves details for a specific project

get_task_details

Retrieves details for a specific timeline task

list_milestones

Lists all project milestones

list_timeline_tasks

Requires a workspace ID. Lists all tasks on the Toggl Plan timeline for a specific workspace

list_workspace_projects

Lists all projects in a specific Toggl Plan workspace

list_workspace_tags

Lists all tags used for task categorization

list_workspace_users

Lists all users with access to the workspace

update_timeline_task

Provide updates as a JSON object. Updates an existing timeline task

Example Prompts for Toggl Plan in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Toggl Plan immediately.

"List all active projects in Workspace 992211."

"Create a timeline task named 'Re-authenticate module' in Project 19332, workspace 992211."

Troubleshooting Toggl Plan MCP Server with Pydantic AI

Common issues when connecting Toggl Plan to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Toggl Plan + Pydantic AI FAQ

Common questions about integrating Toggl Plan MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Toggl Plan MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.