Brandfolder 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 Brandfolder 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 Brandfolder. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Brandfolder?"
)
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 Brandfolder MCP Server
Connect your Brandfolder environment to any AI agent and organize your entire digital asset repository organically through natural conversation.
LlamaIndex agents combine Brandfolder 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 Discovery — List, retrieve, and filter high-resolution brand assets across organizations
- Collections — Map active collections managing internal team sharing structures instantly
- Organizations — Check specific Brandfolder organization topologies
The Brandfolder 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 Brandfolder to LlamaIndex via MCP
Follow these steps to integrate the Brandfolder 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 Brandfolder
Why Use LlamaIndex with the Brandfolder MCP Server
LlamaIndex provides unique advantages when paired with Brandfolder through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Brandfolder tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Brandfolder tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Brandfolder, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Brandfolder tools were called, what data was returned, and how it influenced the final answer
Brandfolder + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Brandfolder MCP Server delivers measurable value.
Hybrid search: combine Brandfolder real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Brandfolder 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 Brandfolder for fresh data
Analytical workflows: chain Brandfolder queries with LlamaIndex's data connectors to build multi-source analytical reports
Brandfolder MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Brandfolder to LlamaIndex via MCP:
create_cms_asset
Inject a new digital asset (image, document, etc.) into a Brandfolder
get_asset_details
` logic. Retrieve extensive metadata for a specific digital asset
get_brandfolder_assets
Search and retrieve digital assets within a specific Brandfolder
get_collection_assets
Search and retrieve digital assets within a specific Collection
list_asset_attachments
Retrieve the actual CDN delivery URLs and attachments stored behind an Asset
list_asset_tags
Retrieve the exact structural matching verifying Tags attached to an asset
list_global_brandfolders
Retrieve all Brandfolders (logical asset containers) in the workspace
list_platform_organizations
Retrieve all top-level tenant organizations accessible by your API key
patch_cms_asset
Update metadata attributes of an existing digital asset
wipe_media_asset
Permanently delete a digital asset from Brandfolder
Example Prompts for Brandfolder in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Brandfolder immediately.
"List the collections available in my main Brandfolder organization."
"Search my assets for any PDF related to standard onboarding manuals."
"Double check my organization ID tied to the user profile."
Troubleshooting Brandfolder MCP Server with LlamaIndex
Common issues when connecting Brandfolder to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBrandfolder + LlamaIndex FAQ
Common questions about integrating Brandfolder 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 Brandfolder 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 Brandfolder to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.