How to Use the Toggl Plan MCP in LangChain

Q: Can I use the MCP Server to manage users in Toggl Plan using LangChain?

Yep. You can call listworkspaceusers to get a list of all people who have access to the workspace. This is useful for checking permissions before running other actions.

Q: How do I delete tasks safely with Toggl Plan and LangChain?

The deletetimelinetask tool permanently removes a task, so you'll need to confirm the action. Your agent needs clear instructions because this process is irreversible.

Q: Does Toggl Plan support tag categorization with LangChain?

Yes. You can call listworkspacetags to get a list of all tags used for task grouping, which helps categorize and filter your project data.

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Connect Toggl Plan MCP to LangChain

Create your Vinkius account to connect Toggl Plan to LangChain 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 Toggl Plan with LangChain

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Managing Tasks with the MCP Server

Use `create_timeline_task` to add a task directly onto the Toggl Plan timeline. You just need the workspace ID, the project ID, and the name for that new task. You can also call `update_timeline_task` if something changes; it takes a full JSON object so you maintain control over every field.

Listing Project Information

Need an overview? The tool `list_workspace_projects` gives you every project available in the workspace. You can follow up by using `list_milestones` to see all key phases for those projects. Alternatively, if you only care about tasks, `list_timeline_tasks` pulls a list of everything assigned within the specified workspace ID.

Retrieving Specific Details

If you know what you're looking for, use `get_project_details` to pull all data on one project. Similarly, `get_task_details` fetches specifics for a single timeline task. These read tools let your agent build complex logic: first getting project scope, then checking related tasks.

Setup guide

Set up Toggl Plan MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Toggl Plan tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

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

async with MultiServerMCPClient({
    "toggl-plan-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Toggl Plan transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Toggl Plan. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Toggl Plan MCP in LangChain

LangChain lets you weave API calls into multi-step pipelines. You can chain actions like listing projects and then using that output to create a new task via the MCP Server.

This server handles project structure data, including workspace IDs, project names, task details, and user access lists. The agent works primarily with structured organizational data.

Yep. You can call `list_workspace_users` to get a list of all people who have access to the workspace. This is useful for checking permissions before running other actions.

The `delete_timeline_task` tool permanently removes a task, so you'll need to confirm the action. Your agent needs clear instructions because this process is irreversible.

Yes. You can call `list_workspace_tags` to get a list of all tags used for task grouping, which helps categorize and filter your project data.

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