Indy MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Form, Create Webhook, Delete Form, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Indy 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 Indy app connector for LlamaIndex is a standout in the Productivity 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 Indy. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Indy?"
)
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 Indy MCP Server
Connect your Indy account to any AI agent and manage forms and records through natural conversation.
LlamaIndex agents combine Indy 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
- Form Management — List all forms, inspect configurations, create new forms, and delete unused ones
- Record Tracking — Browse all form submissions, inspect individual records with full field data
- Template Management — List and inspect form templates for reusable designs
- Group Organization — Browse form groups for organized management
- File Access — List files attached to form submissions
The Indy 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 Indy tools available for LlamaIndex
When LlamaIndex connects to Indy through Vinkius, your AI agent gets direct access to every tool listed below — spanning form-builder, data-collection, freelance-management, 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 form
Create a new webhook
Delete a form
Delete a webhook
Get account status
Get form details
Get submission details
Get user details
List all forms
List form submissions
List connected users
List active webhooks
Connect Indy to LlamaIndex via MCP
Follow these steps to wire Indy 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 Indy MCP Server
LlamaIndex provides unique advantages when paired with Indy through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Indy tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Indy tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Indy, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Indy tools were called, what data was returned, and how it influenced the final answer
Indy + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Indy MCP Server delivers measurable value.
Hybrid search: combine Indy real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Indy 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 Indy for fresh data
Analytical workflows: chain Indy queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Indy in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Indy immediately.
"Show all forms and the latest submissions for the 'Customer Feedback' form."
"Create a new 'Event Registration' form and list available templates."
"Show all records for the bug report form and any attached files."
Troubleshooting Indy MCP Server with LlamaIndex
Common issues when connecting Indy to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpIndy + LlamaIndex FAQ
Common questions about integrating Indy MCP Server with LlamaIndex.