How to Use the ClickTime MCP in LlamaIndex

Q: How does Vinkius protect my ClickTime user profiles?

Your employee names and email addresses pulled via listclicktimeusers never sit on a shared disk. The MCP connection operates through a zero-trust, ephemeral sandbox that spins down the millisecond your query finishes.

Turn your ClickTime data into a searchable vector index with this LlamaIndex MCP Server.

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Connect ClickTime MCP to LlamaIndex

Create your Vinkius account to connect ClickTime to LlamaIndex 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 ClickTime with LlamaIndex

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Index your agency data with this MCP Server

Querying a database for timesheets is boring. LlamaIndex takes the JSON from `list_clicktime_projects` and `list_clicktime_clients` and embeds it into a vector store. Now you have a semantic search engine for your entire company's client roster. When someone asks what projects your team did for a specific client last year, the agent does not guess. It queries the vector space, finds the exact client ID, and retrieves the grounded truth.

RAG for employee time entries

Feeding raw logs into a prompt usually blows up your context window. Instead, you run `get_high_volume_time_report` and chunk those 2500 records into manageable nodes. LlamaIndex handles the embedding automatically. Your query engine can now answer complex questions about resource allocation. It looks up the user via `get_my_clicktime_profile` and cross-references their specific hours against the embedded time logs.

Build a unified project knowledge base

Disconnected data slows teams down. You can pull active work types using `list_clicktime_tasks` and combine that with active assignments from `list_clicktime_jobs`. The framework merges these API responses with your internal company wikis. A project manager just asks the chat interface why a specific deliverable is behind schedule. The system retrieves the exact logged hours for that task and summarizes the discrepancy based on real API data.

Setup guide

Set up ClickTime MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all ClickTime MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to ClickTime tools.",
)
response = await agent.run("List recent ClickTime data")

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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 ClickTime. 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 ClickTime MCP in LlamaIndex

Install the llama-index-tools-mcp package. Create a BasicMCPClient with your Vinkius endpoint URL, pass it to McpToolSpec, and await the async tool list generation.

Yes. You might only want your RAG app to read projects, not pull massive timesheets. Use the allowed tools filter to restrict the agent to just list_clicktime_projects and list_clicktime_tasks.

Not anymore. The tool specification automatically takes the output from endpoints like list_clicktime_users and formats it so your FunctionAgent can read it directly.

APIs require exact IDs and structured queries. Embedding the output of list_time_entries lets you ask fuzzy questions like who spent the most time on design last month and get an answer grounded in actual database records.

Your employee names and email addresses pulled via list_clicktime_users never sit on a shared disk. The MCP connection operates through a zero-trust, ephemeral sandbox that spins down the millisecond your query finishes.

Use it with your favorite AI tools

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