Cloud Assess 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 Cloud Assess as an MCP tool provider through 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 Cloud Assess. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Cloud Assess?"
)
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 Cloud Assess MCP Server
Connect your Cloud Assess account to any AI agent and take full control of your RTO (Registered Training Organisation) operations through natural conversation. Streamline how you manage student progress and assessment compliance natively.
LlamaIndex agents combine Cloud Assess tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Student Oversight — List and retrieve details for all students (members) in your system natively
- Enrolment Intelligence — Access and monitor student enrolments in qualifications and individual units flawlessly
- Assessment Management — List and review assessment results, outcomes, and evidence records securely
- Unit Progress Tracking — Monitor progress and completion status at the unit enrolment level flawlessly
- Form & Checklist Auditing — Access specific assessment forms and data points directly within your workspace flawlessly
- Staff Visibility — List internal trainers and assessors who manage the training delivery flawlessly
The Cloud Assess 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 Cloud Assess to LlamaIndex via MCP
Follow these steps to integrate the Cloud Assess 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 Cloud Assess
Why Use LlamaIndex with the Cloud Assess MCP Server
LlamaIndex provides unique advantages when paired with Cloud Assess through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Cloud Assess tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Cloud Assess tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Cloud Assess, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Cloud Assess tools were called, what data was returned, and how it influenced the final answer
Cloud Assess + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Cloud Assess MCP Server delivers measurable value.
Hybrid search: combine Cloud Assess real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Cloud Assess 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 Cloud Assess for fresh data
Analytical workflows: chain Cloud Assess queries with LlamaIndex's data connectors to build multi-source analytical reports
Cloud Assess MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Cloud Assess to LlamaIndex via MCP:
get_student_details
Get detailed information for a specific student
list_assessment_forms
List specific forms and checklists captured within assessments
list_assessment_records
List individual assessment results and evidence records
list_student_members
List all students (members) in Cloud Assess
list_training_assessors
List all internal assessors and trainers
list_training_enrolments
List student enrolments in qualifications or units
list_training_locations
List physical or logical training locations
list_unit_enrolment_progress
List progress and status at the unit enrolment level
Example Prompts for Cloud Assess in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Cloud Assess immediately.
"List all students currently enrolled in the 'Diploma of Management'."
"Show me the assessment results for student ID 'STU_12345'."
"Who is the assessor assigned to the 'Unit BSB401' for John Doe?"
Troubleshooting Cloud Assess MCP Server with LlamaIndex
Common issues when connecting Cloud Assess to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCloud Assess + LlamaIndex FAQ
Common questions about integrating Cloud Assess 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 Cloud Assess 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 Cloud Assess to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.