How to Use the Alai MCP in LlamaIndex

Q: How do I connect the Alai MCP server to LlamaIndex?

Use the McpToolSpec to wrap the MCP client. This exposes all the Alai tools, like listcampaigns and generatecontent, in a format that LlamaIndex can pass to a FunctionAgent.

Q: Can I search for headshots based on their style with Alai and LlamaIndex?

Yes, if you index that data. When your agent calls generatecontent with a specific template, you can have LlamaIndex store the asset ID along with the template name. Then you can perform semantic searches to find all assets created with a certain style.

Turn your Alai-generated headshots and campaign data into a searchable knowledge base with LlamaIndex.

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Connect Alai MCP to LlamaIndex

Create your Vinkius account to connect Alai to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Alai with LlamaIndex

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Index and Query Your Creative Assets

The Alai MCP Server lets you create AI-generated headshots. With LlamaIndex, you can automatically index the metadata for every asset and campaign you create. Every call to `create_asset` or `create_campaign` generates data that LlamaIndex can ingest. This means you can build a RAG pipeline that answers questions like, "Show me all headshots generated for the Q3 marketing campaign" or "What was the source photo for asset ID 12345?". Your agent queries the indexed data, not a static database.

Build a Self-Documenting MCP Server

Connect LlamaIndex to the Alai tools to build a system that remembers its own operations. When your agent calls `generate_content`, LlamaIndex can index the request parameters and the resulting generation ID. Over time, you build a rich, semantic index of every action taken. This lets you analyze past performance, audit generation history with `list_generations`, and even build agents that learn from previous runs to make better decisions next time.

Ground Agent Responses in Real Data

Stop guessing about the status of your creative assets. A LlamaIndex query engine built on top of the Alai tools provides answers grounded in actual API responses, not hallucinations. Ask your agent, "Are there any headshots using the 'classic' template?" and it will query its index of `list_assets` and `get_asset` results to give you a factual answer. It's a reliable way to check on your marketing collateral.

Setup guide

Set up Alai MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Alai MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Alai tools.",
)
response = await agent.run("List recent Alai data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Alai. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Alai MCP in LlamaIndex

Use the `McpToolSpec` to wrap the MCP client. This exposes all the Alai tools, like `list_campaigns` and `generate_content`, in a format that LlamaIndex can pass to a FunctionAgent.

Yes, if you index that data. When your agent calls `generate_content` with a specific template, you can have LlamaIndex store the asset ID along with the template name. Then you can perform semantic searches to find all assets created with a certain style.

The key difference is turning API outputs into a queryable knowledge base. Instead of just executing a `create_campaign` call, LlamaIndex helps you remember that you did it, so you can ask questions about that campaign later using natural language.

LlamaIndex will primarily index the metadata, not the images themselves. It will store the asset ID, campaign info, creation date, and the URL to the final photo returned by Alai's `get_asset` tool. You can then search this text-based metadata.

Your selfie images are sent to the Alai server for processing and are not stored by LlamaIndex. The Vinkius platform ensures the Alai MCP server handles that image data in a secure, isolated environment for the duration of the generation task only.

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