How to Use the Ghost MCP in LlamaIndex

Q: How do I load Ghost tools into LlamaIndex?

Install llama-index-tools-mcp. Instantiate a BasicMCPClient, wrap it with McpToolSpec, and call totoollistasync() to pass the MCP tools to your FunctionAgent.

Q: Can I restrict which Ghost data LlamaIndex indexes?

Yes. You apply an allowedtools filter when setting up the MCP tool spec. This lets you expose static pages while hiding subscription tiers from the indexing process.

Q: How do I check if the connection is active?

Your agent calls verifyapiconnection before attempting a massive indexing run. This prevents your RAG pipeline from failing halfway through a data pull.

Index your entire Ghost CMS into LlamaIndex vector stores via this MCP Server for grounded RAG applications.

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Connect Ghost MCP to LlamaIndex

Create your Vinkius account to connect Ghost 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 Ghost with LlamaIndex

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Semantic Knowledge Bases via MCP Server

The `list_published_posts` tool allows LlamaIndex to pull your Ghost archive and chunk it into a searchable vector store. Instead of a standard query, your RAG application iterates through `get_post_by_slug` to embed the full text of every article you have ever published. Your users query past content without hitting the Ghost API directly every time. The index holds the semantic meaning of your posts, allowing the agent to answer questions based entirely on your actual publication data.

Author & Tag Graphing

LlamaIndex uses `list_blog_authors` to ingest your team directory into its knowledge graph. When someone asks about a specific writer's expertise, the agent queries the index, which was previously populated by `get_author_details`. The same process applies to your site structure. By running `list_content_tags` and `get_tag_details`, LlamaIndex maps the relationships between your categories, ensuring retrieved documents are contextually linked by their original Ghost taxonomy.

Static Page & Tier Indexing

The `list_static_pages` tool feeds your static pages directly into the LlamaIndex document pipeline. If a reader asks about your policies, the agent retrieves the exact text from `get_page_by_slug` rather than guessing. You also index your monetization setup using `list_subscription_tiers` and `get_site_settings`. This gives your RAG system the context to answer user questions about premium access limits using data from the MCP Server.

Setup guide

Set up Ghost 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 Ghost 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 Ghost tools.",
)
response = await agent.run("List recent Ghost 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 Ghost CMS. 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 Ghost MCP in LlamaIndex

Install `llama-index-tools-mcp`. Instantiate a `BasicMCPClient`, wrap it with `McpToolSpec`, and call `to_tool_list_async()` to pass the MCP tools to your FunctionAgent.

You have to trigger the sync. The agent pulls data on demand, which you then embed and insert into your vector store.

Yes. You apply an `allowed_tools` filter when setting up the MCP tool spec. This lets you expose static pages while hiding subscription tiers from the indexing process.

Your agent calls `verify_api_connection` before attempting a massive indexing run. This prevents your RAG pipeline from failing halfway through a data pull.

If you permit the agent to call the subscription tier tool, that exact pricing data enters your vector database. The system reads author profiles and post bodies, storing them wherever your LlamaIndex instance persists its vectors.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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