How to Use the Clockify MCP in AutoGen

Q: How do I configure AutoGen to use the Clockify MCP Server?

Install autogen-extmcp in your Python environment. You fetch the tools using mcpservertools with a StreamableHttpServerParams object. Pass the resulting list directly to your AssistantAgent.

Q: How does AutoGen know which Clockify workspace to use?

An agent runs listclockifyworkspaces during its initialization phase. It shares the correct workspace ID with the rest of the swarm in the shared chat context.

Build multi-agent systems that debate project allocations and track time in Clockify via AutoGen.

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Connect Clockify MCP to AutoGen

Create your Vinkius account to connect Clockify to AutoGen 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 Clockify with AutoGen

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Perplexity

AutoGen Agents Debate Hours

The `add_new_time_entry` tool executes only after your AutoGen agents reach an agreement. A coding agent reports it spent four hours on a feature, while a project manager agent checks the original estimate. They negotiate the final billable number before touching the API. Once they agree, one agent fires the command to log the work. If the timer is still running, it calls `stop_current_timer` to close it out. You get timesheets backed by an automated peer-review process.

Query the Clockify MCP Server

Calling `list_workspace_projects` gives your agent swarm the current layout of your active work. The system needs this raw data to assign tasks correctly. An operations agent parses the project list and assigns specific IDs to specialized worker agents. They pull `list_workspace_clients` to ensure no one logs time against an inactive account. The agents cross-reference the client roster with their internal instructions. You avoid administrative errors because the bots check each other's math.

Audit Team Capacity

The `list_workspace_users` function feeds your resource management agents. They pull the active directory and iterate through it using `list_user_time_entries`. The swarm builds a complete picture of who is overworked and who has spare cycles. A reporting agent highlights anyone logging more than forty hours. It flags the anomalies and suggests project reassignments to the group. The entire conversation happens autonomously using real data.

Setup guide

Set up Clockify MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Clockify tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Clockify_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Clockify data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Clockify_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Clockify data")
    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 Clockify. 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 Clockify MCP in AutoGen

Install `autogen-ext[mcp]` in your Python environment. You fetch the tools using `mcp_server_tools` with a `StreamableHttpServerParams` object. Pass the resulting list directly to your `AssistantAgent`.

They share the same tool list provided by the MCP Server. You usually designate one specific agent to handle the actual API calls while the others request data from it.

An agent runs `list_clockify_workspaces` during its initialization phase. It shares the correct workspace ID with the rest of the swarm in the shared chat context.

Only if you instruct the agents to monitor it. They can call `stop_current_timer` when they determine a task is complete based on their internal conversation.

Only the specific AutoGen session you authenticate. Vinkius secures the traffic, ensuring your exact timer durations, user emails, and workspace IDs stay locked in a temporary sandbox. Once the multi-agent chat ends, the access disappears.

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