Clockify MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Clockify as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Clockify. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Clockify?"
)
print(response)
asyncio.run(main())
* 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 Clockify MCP Server
Connect your Clockify account to any AI agent and take full control of your time tracking and project management through natural conversation. Streamline how you monitor work hours and team productivity natively.
LlamaIndex agents combine Clockify tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Workspace Oversight — List and retrieve details for all workspaces you have access to natively
- Project Intelligence — Access and monitor all projects and clients configured in your account flawlessly
- Time Tracking — List and retrieve details for all time entries for any user in your team securely
- Timer Management — Start and stop timers directly from your chat interface to ensure accurate logging flawlessly
- Team Logistics — List all users and team members within a workspace to understand allocation securely
- Productivity Auditing — Retrieve detailed time entry metadata including descriptions and project associations flawlessly
The Clockify MCP Server exposes 8 tools through the Vinkius. Connect it to LlamaIndex 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 Clockify to LlamaIndex via MCP
Follow these steps to integrate the Clockify MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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 8 tools from Clockify
Why Use LlamaIndex with the Clockify MCP Server
LlamaIndex provides unique advantages when paired with Clockify through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Clockify tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Clockify tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Clockify, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Clockify tools were called, what data was returned, and how it influenced the final answer
Clockify + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Clockify MCP Server delivers measurable value.
Hybrid search: combine Clockify real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Clockify to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Clockify for fresh data
Analytical workflows: chain Clockify queries with LlamaIndex's data connectors to build multi-source analytical reports
Clockify MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Clockify to LlamaIndex via MCP:
add_new_time_entry
Add a new time entry to a workspace
get_my_clockify_profile
Retrieve information about the authenticated user
list_clockify_workspaces
List all workspaces the user has access to
list_user_time_entries
List time entries for a specific user in a workspace
list_workspace_clients
List all clients configured in a workspace
list_workspace_projects
List all projects within a specific workspace
list_workspace_users
List all users within a specific workspace
stop_current_timer
Stop the currently running timer for a specific user
Example Prompts for Clockify in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Clockify immediately.
"List all my Clockify workspaces."
"Show me the last 5 time entries for user 'John Doe'."
"Stop my running timer in the 'Engineering' workspace."
Troubleshooting Clockify MCP Server with LlamaIndex
Common issues when connecting Clockify to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpClockify + LlamaIndex FAQ
Common questions about integrating Clockify MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Clockify with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Clockify to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.