How to Use the Toggl Plan MCP in LangChain

Q: Can I list all projects using Toggl Plan and LangChain?

Yep. You just run listworkspaceprojects. This gives your agent a complete manifest of every project in the workspace, which you can then use as input for subsequent steps.

Q: Does Toggl Plan support Milestone tracking with LangChain?

Absolutely. You can list all key dates using listmilestones. This lets your agent track major project phases alongside the day-to-day tasks you create or update.

Q: What happens if I need to delete a task with Toggl Plan and LangChain?

You use deletetimelinetask. Just remember, that action is irreversible. The agent forces you to confirm the permanent removal of the segment before running it.

Automate complex scheduling logic and project tracking using LangChain.

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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

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build multi-step planning chains

You can chain together multiple actions to model full work cycles. For instance, first use `list_workspace_projects` to find all active initiatives. Then, your agent automatically runs `get_timeline_view` for a specific date range. This flow lets the agent decide *when* and *how* to create new segments using `create_timeline_task`, making multi-step scheduling reliable.

Manage team scope and resources

Need to know who's involved before building a timeline? Run `list_workspace_members` first. Then, check out what projects exist using `list_workspace_projects`. This gives your agent all the necessary context. The chain can then use that data to call other tools, like listing relevant tags via `list_workspace_tags`, keeping everything self-contained.

Update and refine existing schedules

Sometimes a plan shifts. The agent runs `get_task_details` on an old task to see what's wrong. It then takes that data, modifies it, and pushes the correction using `update_timeline_task`. This ensures the entire MCP Server operation is traceable from read to write.

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-1-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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Common questions about Toggl Plan MCP in LangChain

You can trace every step in your scheduling process. By chaining tools like `get_task_details` and `update_timeline_task`, you get full observability into the data changes.

Yep. You just run `list_workspace_projects`. This gives your agent a complete manifest of every project in the workspace, which you can then use as input for subsequent steps.

Absolutely. You can list all key dates using `list_milestones`. This lets your agent track major project phases alongside the day-to-day tasks you create or update.

You use `delete_timeline_task`. Just remember, that action is irreversible. The agent forces you to confirm the permanent removal of the segment before running it.

The server handles timeline task data, including names, start dates, end dates, and associated project information. Your agent processes these structured scheduling details.

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