AssessTEAM MCP Server for LlamaIndexGive LlamaIndex instant access to 7 tools to Create Timesheet Entry, Get Profitability Report, List Employees, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add AssessTEAM 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 AssessTEAM app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 7 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 AssessTEAM. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in AssessTEAM?"
)
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 AssessTEAM MCP Server
Connect your AssessTEAM account to any AI agent and simplify how you manage employee evaluations, project timesheets, and organizational profitability through natural conversation.
LlamaIndex agents combine AssessTEAM tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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
- Performance Management — List and query employee evaluations and KPI assessments to track workforce development.
- Timesheet Control — Create and list time logs for project tracking to ensure accurate labor reporting.
- Project Profitability — Retrieve detailed financial reports and margin analysis for your active projects.
- Team Directory — List employees, teams, and organizational structures to manage your workforce hierarchy.
- Project Oversight — Monitor all current projects and their associated profitability metrics in real-time.
- Compliance & Reporting — Fetch history of recorded time logs and evaluations directly via AI commands.
The AssessTEAM MCP Server exposes 7 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 7 AssessTEAM tools available for LlamaIndex
When LlamaIndex connects to AssessTEAM through Vinkius, your AI agent gets direct access to every tool listed below — spanning performance-management, employee-evaluation, timesheet-tracking, 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.
Create a new timesheet entry
Get project profitability report
List team employees
List organizational teams
List performance evaluations
List AssessTEAM projects
List timesheet entries
Connect AssessTEAM to LlamaIndex via MCP
Follow these steps to wire AssessTEAM 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 AssessTEAM MCP Server
LlamaIndex provides unique advantages when paired with AssessTEAM through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine AssessTEAM tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain AssessTEAM tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query AssessTEAM, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what AssessTEAM tools were called, what data was returned, and how it influenced the final answer
AssessTEAM + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the AssessTEAM MCP Server delivers measurable value.
Hybrid search: combine AssessTEAM real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query AssessTEAM 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 AssessTEAM for fresh data
Analytical workflows: chain AssessTEAM queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for AssessTEAM in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with AssessTEAM immediately.
"List all active projects and their status."
"Log 8 hours for employee 'emp_1029' on project 'proj_8823' for today."
"Show me the latest performance evaluations."
Troubleshooting AssessTEAM MCP Server with LlamaIndex
Common issues when connecting AssessTEAM to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAssessTEAM + LlamaIndex FAQ
Common questions about integrating AssessTEAM MCP Server with LlamaIndex.