GAN.ai MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GAN.ai 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 MCP SERVER
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 GAN.ai. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in GAN.ai?"
)
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 GAN.ai MCP Server
Connect your GAN.ai account to any AI agent to automate your personalized video marketing and sales outreach through the Model Context Protocol (MCP). GAN.ai is a leading generative AI platform that enables brands to create thousands of unique videos with custom names, locations, and details. This MCP server enables you to trigger video generation, monitor real-time processing status, and retrieve landing page links directly through natural conversation.
LlamaIndex agents combine GAN.ai 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.
Key Features
- Personalized Video Generation — Trigger bulk video generation based on project templates and dynamic tags (e.g., first name, company).
- Real-time Status Monitoring — Track the asynchronous processing of your video requests and retrieve final MP4 and landing page URLs.
- Project Oversight — List all video templates/projects and fetch detailed variable definitions for personalization.
- Campaign Discovery — Access your history of generated videos and monitor their status (pending, processing, completed).
- Landing Page Integration — Retrieve branded landing page permalinks for each generated video to fuel your outreach sequences.
- Engagement Analytics — Fetch view counts and engagement metrics for specific videos to measure campaign success.
- Webhook Visibility — List configured webhooks to ensure your systems are receiving real-time generation notifications.
- Real-time Synchronization — Keep your generative video strategy accessible to your AI assistant without leaving your primary workspace.
The GAN.ai 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.
How to Connect GAN.ai to LlamaIndex via MCP
Follow these steps to integrate the GAN.ai 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 12 tools from GAN.ai
Why Use LlamaIndex with the GAN.ai MCP Server
LlamaIndex provides unique advantages when paired with GAN.ai through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GAN.ai tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GAN.ai tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GAN.ai, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GAN.ai tools were called, what data was returned, and how it influenced the final answer
GAN.ai + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GAN.ai MCP Server delivers measurable value.
Hybrid search: combine GAN.ai real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GAN.ai 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 GAN.ai for fresh data
Analytical workflows: chain GAN.ai queries with LlamaIndex's data connectors to build multi-source analytical reports
GAN.ai MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect GAN.ai to LlamaIndex via MCP:
generate_personalized_videos
Generate videos in bulk
generate_single_video
Generate one video
get_generation_status
Check video status
get_project_metadata
Get template schema
get_video_metadata
Get video details
get_video_stats
Get engagement stats
get_workspace_info
ai workspace. Get workspace details
list_configured_webhooks
List active webhooks
list_generated_videos
List video history
list_landing_templates
List landing pages
list_video_projects
List video templates
verify_api_connection
ai API connectivity. Verify API access
Example Prompts for GAN.ai in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GAN.ai immediately.
"List all my available video projects in GAN.ai."
"Generate a personalized video for 'John Doe' (johndoe@email.com) using project 'proj_123'."
"Check the status of video generation 'inf_abc789'."
Troubleshooting GAN.ai MCP Server with LlamaIndex
Common issues when connecting GAN.ai to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGAN.ai + LlamaIndex FAQ
Common questions about integrating GAN.ai 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 GAN.ai 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 GAN.ai to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.