How to Use the HubSpot MCP in LlamaIndex

Q: Can LlamaIndex create new HubSpot records?

Yes. Your agent can execute createcontact or linkcrmobjects based on the context of a conversation. It reads the intent and pushes the data back to the CRM.

Q: How do I filter which tools my agent can use?

Pass an allowedtools list when configuring your McpToolSpec. This restricts the agent to specific actions, like only allowing read operations.

Index your HubSpot deals and contacts into LlamaIndex vector stores to build semantic search over your live CRM data.

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Connect HubSpot MCP to LlamaIndex

Create your Vinkius account to connect HubSpot 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 HubSpot with LlamaIndex

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Ground RAG apps with HubSpot MCP Server data

`get_deal_details` and `get_company_info` pull live CRM records directly into your LlamaIndex pipelines. Instead of relying on stale exports, your AI client queries the API in real time. It grabs the exact state of a sales pipeline and feeds it straight into your context window. This means your semantic search actually reflects reality. When a user asks about a specific account, the agent retrieves the live data, indexes it alongside your internal documents, and returns an answer based on facts.

Index bulk CRM records for semantic search

`list_contacts` and `list_deals` allow your application to ingest massive amounts of structured data. You pull the records, convert them into nodes, and embed them into your vector store. Suddenly, your sales team can search their entire database using natural language. They just ask questions, and LlamaIndex handles the retrieval by matching their query against the embedded HubSpot data.

Dynamic schema mapping for custom fields

`get_object_schema` reads your HubSpot configuration so your index understands custom properties. You run this tool first, and LlamaIndex learns exactly how your CRM is structured before it tries to extract data. Manual index mapping becomes a thing of the past. The agent discovers new fields automatically, ensuring your RAG application always has the complete picture of your data.

Setup guide

Set up HubSpot 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 HubSpot 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 HubSpot tools.",
)
response = await agent.run("List recent HubSpot data")

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Common questions about HubSpot MCP in LlamaIndex

You initialize a BasicMCPClient with your Vinkius URL. The platform manages the authentication, so you just pass the resulting tools to your FunctionAgent.

Yes. Your agent can execute `create_contact` or `link_crm_objects` based on the context of a conversation. It reads the intent and pushes the data back to the CRM.

It indexes the data into your chosen vector store. You control how often the agent calls `search_contacts` to refresh those embeddings.

Pass an allowed_tools list when configuring your McpToolSpec. This restricts the agent to specific actions, like only allowing read operations.

The connection operates on a zero-trust architecture. Your company names, domains, and associated contact lists are processed in an isolated environment that requires explicit token verification for every single request.

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