How to Use the HubSpot CMS Hub MCP in LlamaIndex
Index your HubSpot CMS Hub site pages and blog metadata directly into LlamaIndex for semantic search and grounded RAG applications.
Works with every AI agent you already use
…and any MCP-compatible client
Connect HubSpot CMS Hub MCP to LlamaIndex
Create your Vinkius account to connect HubSpot CMS Hub 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.
Embed HubSpot Blog Posts
`hs_get_blog_post` extracts the full body content length, slug, and SEO settings so LlamaIndex can embed the data into your vector store. Your RAG application now answers queries based on your actual published articles instead of guessing. When a user asks about a specific topic, the engine runs `hs_search_blog_posts` to find exact matches in your library. It pulls the text, chunks it, and adds it to the index for immediate retrieval.
Index Site Pages
`hs_list_site_pages` retrieves your standard website page inventory so your LlamaIndex knowledge base understands your site structure. It maps the URL slugs and publish states for every page hosted on your domain. You configure the `McpToolSpec` to feed this layout straight into a `FunctionAgent`. The agent cross-references your HubSpot about and pricing pages against internal documents to ensure your external messaging matches your internal wikis.
Filter by Tag with MCP Server
`hs_list_blog_tags` grabs your taxonomy and URL clusters to build a structured metadata filter for your index. This MCP Server gives your RAG system the exact vocabulary your marketing team uses. If a query requires author context, the agent triggers `hs_list_blog_authors`. It links the embedded content chunks to the specific writer's email and biography, making your semantic search aware of who wrote what in HubSpot.
Set up HubSpot CMS Hub 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 HubSpot CMS Hub 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 HubSpot CMS Hub tools.",
)
response = await agent.run("List recent HubSpot CMS Hub data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HubSpot. 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 HubSpot CMS Hub MCP in LlamaIndex
Use it with your favorite AI tools
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