Innform MCP Server for LlamaIndexGive LlamaIndex instant access to 9 tools to Freeze User, Get User Details, Invite User, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Innform 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 Innform app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 9 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 Innform. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Innform?"
)
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 Innform MCP Server
Connect your Innform training portal to any AI agent and take full control of your Learning Management System (LMS) and employee compliance workflows through natural conversation.
LlamaIndex agents combine Innform tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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
- User Lifecycle Orchestration — List all learners and admins, retrieve detailed high-fidelity profile metadata, and invite new users programmatically
- Assignment Intelligence — Programmatically monitor completed and overdue training assignments to maintain a perfectly coordinated compliance overview
- Training Group Architecture — Access your complete directory of learner groups and their properties to oversee your organizational training structure
- Access Control Management — Programmatically freeze or unfreeze learner accounts to manage platform access dynamically based on organizational needs
- Operational Monitoring — Verify API connectivity and monitor training progress directly through your agent for instant performance reporting
The Innform MCP Server exposes 9 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 9 Innform tools available for LlamaIndex
When LlamaIndex connects to Innform through Vinkius, your AI agent gets direct access to every tool listed below — spanning lms, employee-training, compliance-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.
Freeze a user account
Get details for a specific user
Invite a new learner
List completed training assignments
List learner groups
List overdue training assignments
List Innform users
Unfreeze a user account
Update an existing user
Connect Innform to LlamaIndex via MCP
Follow these steps to wire Innform 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 Innform MCP Server
LlamaIndex provides unique advantages when paired with Innform through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Innform tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Innform tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Innform, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Innform tools were called, what data was returned, and how it influenced the final answer
Innform + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Innform MCP Server delivers measurable value.
Hybrid search: combine Innform real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Innform 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 Innform for fresh data
Analytical workflows: chain Innform queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Innform in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Innform immediately.
"List all active learners in my Innform portal."
"Show me all overdue training assignments for the Engineering team."
"Freeze account for learner ID 'user_123' immediately."
Troubleshooting Innform MCP Server with LlamaIndex
Common issues when connecting Innform to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpInnform + LlamaIndex FAQ
Common questions about integrating Innform MCP Server with LlamaIndex.