MediaSilo MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add MediaSilo as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 MediaSilo. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in MediaSilo?"
)
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 MediaSilo MCP Server
Connect your MediaSilo (Shift) account to any AI agent and take full control of your media asset management and collaboration through natural conversation.
LlamaIndex agents combine MediaSilo tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Asset Management — List all media assets, search by term, and fetch detailed metadata for videos and images
- Project Organization — Enumerate active projects, list folders, and inspect specific project configurations
- Collaboration — Manage Quicklinks for secure media sharing and review with your team and clients
- User Inventory — List authorized users and manage access within your MediaSilo workspace
The MediaSilo MCP Server exposes 10 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.
How to Connect MediaSilo to LlamaIndex via MCP
Follow these steps to integrate the MediaSilo MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from MediaSilo
Why Use LlamaIndex with the MediaSilo MCP Server
LlamaIndex provides unique advantages when paired with MediaSilo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine MediaSilo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain MediaSilo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query MediaSilo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what MediaSilo tools were called, what data was returned, and how it influenced the final answer
MediaSilo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the MediaSilo MCP Server delivers measurable value.
Hybrid search: combine MediaSilo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query MediaSilo 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 MediaSilo for fresh data
Analytical workflows: chain MediaSilo queries with LlamaIndex's data connectors to build multi-source analytical reports
MediaSilo MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect MediaSilo to LlamaIndex via MCP:
get_asset
Get details for a specific asset
get_project
Get details for a specific project
get_project_assets
List all assets within a project
get_quicklink
Get details for a specific Quicklink
list_assets
) from MediaSilo. List all media assets
list_folders
List folders within a project
list_projects
List all projects
list_quicklinks
List all Quicklinks
list_users
List all users
search_assets
Search for assets by term
Example Prompts for MediaSilo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with MediaSilo immediately.
"List the most recent assets in MediaSilo."
"Show folders for project 'Fall Campaign'."
"Search for assets matching 'logo'."
Troubleshooting MediaSilo MCP Server with LlamaIndex
Common issues when connecting MediaSilo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMediaSilo + LlamaIndex FAQ
Common questions about integrating MediaSilo MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect MediaSilo with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect MediaSilo to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.