Ziflow MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Proof, Create Webhook, Get Account Info, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Ziflow 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 Ziflow app connector for LlamaIndex is a standout in the Industry Titans 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 Ziflow. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Ziflow?"
)
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 Ziflow MCP Server
Connect your Ziflow account to any AI agent to automate your creative review and approval processes through natural conversation.
LlamaIndex agents combine Ziflow 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
- Proof Management — Search for proofs, track versions, and monitor review statuses across your entire organization.
- Reviewer Experience — Generate secure viewer URLs for reviewers and manage contacts/team users efficiently.
- Decision Tracking — Submit approval decisions and manage integration properties for cross-platform synchronization.
- Real-time Events — Configure and monitor webhooks to stay updated on proofing events in real-time.
- Asset Organization — Manage assets associated with product SKUs or project codes directly through the AI interface.
The Ziflow 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 Ziflow tools available for LlamaIndex
When LlamaIndex connects to Ziflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning online-proofing, creative-workflow, content-review, 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 proof
created. Create a new webhook
Get account profile
Find contact by email
Get proof details
Generate review link
List proof folders
List proof metadata
List all users
List active webhooks
Search for proofs
Submit proof decision
Connect Ziflow to LlamaIndex via MCP
Follow these steps to wire Ziflow 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 Ziflow MCP Server
LlamaIndex provides unique advantages when paired with Ziflow through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Ziflow tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Ziflow tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Ziflow, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Ziflow tools were called, what data was returned, and how it influenced the final answer
Ziflow + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Ziflow MCP Server delivers measurable value.
Hybrid search: combine Ziflow real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Ziflow 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 Ziflow for fresh data
Analytical workflows: chain Ziflow queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Ziflow in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Ziflow immediately.
"Search for all active proofs in Ziflow."
"Generate a viewer link for proof ID '12345'."
Troubleshooting Ziflow MCP Server with LlamaIndex
Common issues when connecting Ziflow to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpZiflow + LlamaIndex FAQ
Common questions about integrating Ziflow MCP Server with LlamaIndex.