How to Use the Denim MCP in LlamaIndex
Index live Denim campaign metrics and contacts directly into your LlamaIndex RAG pipelines.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Denim MCP to LlamaIndex
Create your Vinkius account to connect Denim 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.
Index Denim campaign data for semantic search
The Denim MCP Server exposes campaign data that LlamaIndex indexes directly into your vector store for semantic search. When your agent calls `get_campaign_details` or `list_marketing_campaigns`, the output goes straight into your vector store. This means you can query your past marketing performance semantically. Your agent searches through old campaign configurations to find what worked, grounding its answers in actual Denim data instead of hallucinating.
Query audience segments using LlamaIndex RAG
This Denim integration lets LlamaIndex query your audience segments and turn raw JSON into searchable documents. Your LlamaIndex agent uses `list_audience_segments` to retrieve your current marketing groups, turning that raw JSON into queryable documents. You can ask the agent complex questions about who you are targeting. It cross-references the retrieved segments with active leads from `list_crm_contacts` to find gaps in your outreach strategy.
Ground marketing decisions in Denim MCP Server metrics
The Denim MCP Server feeds live performance metrics directly into your LlamaIndex RAG pipelines. The agent calls `get_campaign_analytics` to pull open rates and conversions, then indexes those metrics to inform future copy generation. If a campaign is underperforming, the agent detects it through the indexed data. It then pulls fresh assets using `list_email_templates` to suggest highly relevant, data-backed alternatives.
Set up Denim MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 Denim MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 Denim tools.",
)
response = await agent.run("List recent Denim data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Denim. 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 Denim MCP in LlamaIndex
Use it with your favorite AI tools
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