Cincopa MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Cincopa 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 Cincopa. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Cincopa?"
)
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 Cincopa MCP Server
Connect your Cincopa account to any AI agent and take full control of your video and media management through natural conversation. Streamline how you host and distribute content.
LlamaIndex agents combine Cincopa 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
- Gallery Oversight — List and retrieve details for all media galleries and folders natively
- Asset Intelligence — Access detailed metadata for videos, images, and audio files flawlessly
- Upload Automation — Retrieve temporary upload URLs to push new content to your platform securely
- Template Management — List available gallery templates to ensure consistent branding flawlessly
- Content Control — Create new galleries and delete unwanted assets directly from your chat interface flawlessly
- Engagement Monitoring — Monitor media performance and usage metadata directly within your workspace
The Cincopa 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.
How to Connect Cincopa to LlamaIndex via MCP
Follow these steps to integrate the Cincopa 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 8 tools from Cincopa
Why Use LlamaIndex with the Cincopa MCP Server
LlamaIndex provides unique advantages when paired with Cincopa through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Cincopa tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Cincopa tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Cincopa, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Cincopa tools were called, what data was returned, and how it influenced the final answer
Cincopa + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Cincopa MCP Server delivers measurable value.
Hybrid search: combine Cincopa real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Cincopa 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 Cincopa for fresh data
Analytical workflows: chain Cincopa queries with LlamaIndex's data connectors to build multi-source analytical reports
Cincopa MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Cincopa to LlamaIndex via MCP:
create_new_gallery
Create a new media gallery using a template
delete_media_asset
Permanently delete a media asset from the account
get_asset_metadata
Get detailed metadata for a specific media asset
get_gallery_details
Get detailed information for a specific gallery
get_media_upload_url
Retrieve a temporary URL for uploading new media files
list_cincopa_assets
List all media assets (videos, images, audio)
list_cincopa_galleries
List all media galleries in the account
list_cincopa_templates
List available gallery templates
Example Prompts for Cincopa in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Cincopa immediately.
"List all my video galleries in Cincopa."
"Show me the metadata for asset RID 'AAAAtAURG'."
"Create a new gallery called 'Customer Interviews' using the 'Video Portal' template."
Troubleshooting Cincopa MCP Server with LlamaIndex
Common issues when connecting Cincopa to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCincopa + LlamaIndex FAQ
Common questions about integrating Cincopa 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 Cincopa 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 Cincopa to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.