Spiritme MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Spiritme Status, Delete Video, Generate Audio, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Spiritme 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 Spiritme app connector for LlamaIndex is a standout in the Marketing Automation 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 Spiritme. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Spiritme?"
)
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 Spiritme MCP Server
Connect your Spiritme account to any AI agent and take full control of your automated video avatar generation and high-fidelity personalized media workflows through natural conversation.
LlamaIndex agents combine Spiritme 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.
What you can do
- Avatar Portfolio Orchestration — List and manage your entire high-fidelity portfolio of digital avatars programmatically, retrieving detailed technical metadata and SKU IDs
- Video Generation Intelligence — Programmatically trigger and monitor high-fidelity video generation jobs using custom scripts and voice selections
- Asset & Media Architecture — Access your complete directory of high-fidelity hosted video assets to oversee your organizational resource allocation in real-time
- Engagement Monitoring — Access real-time status updates for video processing and track generation results directly through your agent for instant reporting
- Operational Monitoring — Verify account-level API connectivity and monitor video orchestration volume directly through your agent for perfectly coordinated service scaling
The Spiritme 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 Spiritme tools available for LlamaIndex
When LlamaIndex connects to Spiritme through Vinkius, your AI agent gets direct access to every tool listed below — spanning ai-avatars, video-generation, digital-human, 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.
Verify connectivity
Delete a video
Generate audio
Generate a video
Get avatar details
Get video job status
Get template details
Get voice details
List avatars
List templates
List videos
List voices
Connect Spiritme to LlamaIndex via MCP
Follow these steps to wire Spiritme 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 Spiritme MCP Server
LlamaIndex provides unique advantages when paired with Spiritme through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Spiritme tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Spiritme tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Spiritme, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Spiritme tools were called, what data was returned, and how it influenced the final answer
Spiritme + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Spiritme MCP Server delivers measurable value.
Hybrid search: combine Spiritme real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Spiritme 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 Spiritme for fresh data
Analytical workflows: chain Spiritme queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Spiritme in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Spiritme immediately.
"Generate a video with avatar 'av_123' and script: 'Hello, welcome to our team!'."
"Check the status of video job 'job_xyz789'."
"List all active videos in my Spiritme library."
Troubleshooting Spiritme MCP Server with LlamaIndex
Common issues when connecting Spiritme to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSpiritme + LlamaIndex FAQ
Common questions about integrating Spiritme MCP Server with LlamaIndex.