Mokaform MCP Server for LlamaIndexGive LlamaIndex instant access to 8 tools to Create Form, Delete Response, Get Form, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mokaform 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 Mokaform app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 8 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 Mokaform. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Mokaform?"
)
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 Mokaform MCP Server
Connect your Mokaform account to any AI agent and manage AI-powered forms through natural conversation.
LlamaIndex agents combine Mokaform 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
- Form Management — Create, update, and list forms
- Response Collection — Browse and read form submissions
- Workspace Management — Organize forms across multiple workspaces
- Response Actions — View individual responses or delete them
The Mokaform 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.
All 8 Mokaform tools available for LlamaIndex
When LlamaIndex connects to Mokaform through Vinkius, your AI agent gets direct access to every tool listed below — spanning form-builder, data-collection, survey-automation, 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
Delete a form response
Get form details
Get specific response details
List all forms
List all responses for a form
List all workspaces
Update an existing form
Connect Mokaform to LlamaIndex via MCP
Follow these steps to wire Mokaform 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 Mokaform MCP Server
LlamaIndex provides unique advantages when paired with Mokaform through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mokaform tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mokaform tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mokaform, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mokaform tools were called, what data was returned, and how it influenced the final answer
Mokaform + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mokaform MCP Server delivers measurable value.
Hybrid search: combine Mokaform real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mokaform 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 Mokaform for fresh data
Analytical workflows: chain Mokaform queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Mokaform in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Mokaform immediately.
"List all forms and show their response counts."
"Show the latest 3 responses for the Customer Feedback form."
"Create a new feedback form in the Marketing workspace."
Troubleshooting Mokaform MCP Server with LlamaIndex
Common issues when connecting Mokaform to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMokaform + LlamaIndex FAQ
Common questions about integrating Mokaform MCP Server with LlamaIndex.