Worksection MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Complete Task, Create Task, Get Project Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Worksection as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Worksection app connector for LlamaIndex is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Worksection. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Worksection?"
)
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 Worksection MCP Server
Connect your Worksection account to any AI agent to automate your project management and team productivity workflows. Worksection provides a comprehensive set of tools for managing tasks, tracking time, and monitoring real-time project activities through natural conversation.
LlamaIndex agents combine Worksection tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through 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
- Project Lifecycle Management — List all projects, create new ones, and manage tasks across your entire organization programmatically.
- Time Tracking & Timers — Monitor active timers for team members and stop time trackers directly from the AI interface.
- Activity Monitoring — Retrieve a detailed event log of recent account activities to stay updated on project changes and completions.
- Stakeholder Collaboration — Access task comments, project members, and attached files to maintain a clear overview of team collaboration.
- Hierarchical Oversight — Navigate project folders and task sub-trees using simple natural language commands.
The Worksection MCP Server exposes 12 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.
All 12 Worksection tools available for LlamaIndex
When LlamaIndex connects to Worksection through Vinkius, your AI agent gets direct access to every tool listed below — spanning task-management, time-tracking, project-collaboration, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Finish a task
Add new task
Get project info
Get full task info
Check running timers
List company users
List team on project
List tasks in project
List workspace projects
Get event log
Restore a task
Finish time tracking
Connect Worksection to LlamaIndex via MCP
Follow these steps to wire Worksection into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Worksection MCP Server
LlamaIndex provides unique advantages when paired with Worksection through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Worksection tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Worksection tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Worksection, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Worksection tools were called, what data was returned, and how it influenced the final answer
Worksection + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Worksection MCP Server delivers measurable value.
Hybrid search: combine Worksection real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Worksection 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 Worksection for fresh data
Analytical workflows: chain Worksection queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Worksection in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Worksection immediately.
"List all my active project folders in Worksection."
"Show me the last 10 events from my account activity log."
Troubleshooting Worksection MCP Server with LlamaIndex
Common issues when connecting Worksection to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWorksection + LlamaIndex FAQ
Common questions about integrating Worksection MCP Server with LlamaIndex.