How to Use the Substack MCP in LlamaIndex

Q: Can I analyze past subscriber data with Substack and LlamaIndex?

Yes, by indexing the results of listsubscribers. This gives you a searchable record of audience growth patterns over time. It’s much better than just running a live API call.

Q: What specific data types does the MCP Server touch regarding privacy?

The server touches subscriber details when calling listsubscribers, which is then stored and indexed. It also handles post metadata from getpost.

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Connect Substack MCP to LlamaIndex

Create your Vinkius account to connect Substack to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Substack with LlamaIndex

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Advanced Knowledge Retrieval from Substack via LlamaIndex

LlamaIndex turns raw data into context. You can run `get_post_stats` and index the results, meaning you won't hallucinate metrics later. Your agent queries this stored knowledge base to answer specific questions about performance.

Creating a Substack Content Index using LlamaIndex MCP Server

You build your RAG application by indexing content details. Call `list_posts` and pass the output directly into your index. Later, you can query this unified index to find all relevant posts based on semantic meaning, not just keywords.

Tracking Audience Trends with Substack and LlamaIndex

Instead of temporary calls, use `list_subscribers` to populate a persistent knowledge store. This allows your agent to answer historical questions like, 'What was the subscriber count in Q3?' by querying the stored API data.

Setup guide

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

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Common questions about Substack MCP in LlamaIndex

LlamaIndex indexes the outputs of the MCP Server. This means every call—like `get_post_stats`—is stored as factual context, letting your agent answer questions grounded in actual data.

It's perfect for deep content analysis. You index post information via `get_post` and then query that massive index to compare writing styles or topics across your entire catalog.

Yes, by indexing the results of `list_subscribers`. This gives you a searchable record of audience growth patterns over time. It’s much better than just running a live API call.

It supports it. The developer can combine the Substack tools with other APIs, indexing all outcomes into one unified knowledge index for maximum query flexibility.

The server touches subscriber details when calling `list_subscribers`, which is then stored and indexed. It also handles post metadata from `get_post`.

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