Simian MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Add Project Comment, Create Reel, Delete Media, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Simian 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 Simian 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 Simian. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Simian?"
)
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 Simian MCP Server
The Simian MCP server enables your AI agent to manage your creative workflows. Retrieve media links, orchestrate review processes, and analyze viewer engagement directly from the chat interface.
LlamaIndex agents combine Simian 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.
The Simian 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 Simian tools available for LlamaIndex
When LlamaIndex connects to Simian through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-sharing, creative-workflow, media-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.
Add a new comment or approval status to a file
Create a new reel
Permanently remove a file from the library
Retrieve account details and usage statistics
Get metadata for a specific media file
Retrieve comments and annotations for a project file
Get details of a specific reel
List all media files in the library
List all active review and approval projects
List all created reels (presentations)
Send a reel to recipients via email or short link
Update metadata for a media file
Connect Simian to LlamaIndex via MCP
Follow these steps to wire Simian 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 Simian MCP Server
LlamaIndex provides unique advantages when paired with Simian through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Simian tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Simian tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Simian, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Simian tools were called, what data was returned, and how it influenced the final answer
Simian + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Simian MCP Server delivers measurable value.
Hybrid search: combine Simian real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Simian 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 Simian for fresh data
Analytical workflows: chain Simian queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Simian in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Simian immediately.
"Get the review link for project 'Summer Campaign'."
"Summarize the analytics for my latest reel."
"Invite 'client@brand.com' to review project 104."
Troubleshooting Simian MCP Server with LlamaIndex
Common issues when connecting Simian to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSimian + LlamaIndex FAQ
Common questions about integrating Simian MCP Server with LlamaIndex.