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Substack MCP Server: Hyper-Personalized Content at Scale - MCP Implementation

Substack MCP Server: Hyper-Personalized Content at Scale

Substack MCP Server: Seamlessly integrate Claude AI into your Substack workflows, unlocking hyper-personalized content at scale for engaged audiences.

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82% of users reported increased productivity after just one week

About Substack MCP Server

What is Substack MCP Server: Hyper-Personalized Content at Scale?

The Substack MCP Server is a specialized integration that bridges Substack's content ecosystem with AI assistants like Claude. Built using Anthropic's Model Context Protocol (MCP), this server enables AI systems to access and analyze Substack newsletters, posts, and user data programmatically. By converting the Substack API into an MCP-compliant service, it empowers AI tools to deliver highly personalized content recommendations and insights at scale.

How to Use Substack MCP Server: Hyper-Personalized Content at Scale?

Deploying the server involves three core steps:

  1. Installation: Clone the GitHub repository, set up a Python virtual environment, and install dependencies using either traditional pip commands or the streamlined uv tool.
  2. Configuration: Edit the claude_desktop_config.json file to register the server's command path under the mcpServers section.
  3. Interaction: Query the server via Claude for Desktop using natural language requests like "Find AI ethics articles across tech newsletters" or "Show me posts from Stratechery about platform unbundling."

Substack MCP Server Features

Key Features of Substack MCP Server: Hyper-Personalized Content at Scale?

  • Cross-Publication Search: Perform simultaneous keyword searches across multiple Substack newsletters
  • Content Discovery: Surface top-rated newsletters by categories like technology, economics, and culture
  • Author Intelligence: Retrieve detailed profile information for Substack creators
  • Content Metadata: Access post timestamps, tags, and engagement metrics alongside full-text content
  • Custom Tool Extension: Developers can add new API capabilities using the MCP decorator pattern

Use Cases of Substack MCP Server: Hyper-Personalized Content at Scale?

Practical applications include:

  • Market Research: Compare how different newsletters cover breaking tech trends
  • Content Curation: Build personalized reading lists using AI-driven recommendations
  • Author Outreach: Identify top creators in specific niches for partnership opportunities
  • Competitive Analysis: Track coverage patterns across competitor publications
  • Educational Tools: Create topic-specific learning paths using aggregated newsletter content

Substack MCP Server FAQ

FAQ from Substack MCP Server: Hyper-Personalized Content at Scale?

  • Q: Does this work with other AI platforms besides Claude?
    A: Currently MCP is Anthropic-specific, but extension to other platforms is possible through API adaptation
  • Q: How are search results prioritized?
    A: Results use Substack's native ranking algorithms combined with keyword relevance scoring
  • Q: What authentication is required?
    A: No API keys are needed as the server interacts directly with public Substack content
  • Q: Can I limit search scope to specific newsletters?
    A: Yes - specify publication URLs in search queries to constrain results
  • Q: How are updates handled?
    A: The server automatically fetches fresh content from Substack's API endpoints

Content

Substack MCP Server

A Model Context Protocol (MCP) server that enables Claude and other AI assistants to interact with Substack newsletters, posts, and user profiles.

Overview

This project converts the Substack API library into an Anthropic MCP server, allowing Claude to:

  • Retrieve newsletter posts, podcasts, and recommendations
  • Get user profile information and subscriptions
  • Fetch post content and metadata
  • Search for posts within newsletters
  • Search across multiple Substack newsletters simultaneously
  • Discover popular Substack newsletters by category

Installation

Prerequisites

Installation Steps

# Clone the repository
git clone https://github.com/Greg-Swiftomatic/substack-mcp-server.git
cd substack-mcp-server

# Set up virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Alternatively, you can use uv:

# Using uv for faster installation
curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt

Usage

Running the Server

python substack_mcp.py

Connecting to Claude for Desktop

  1. Open your Claude for Desktop configuration file:
* MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
* Windows: `%APPDATA%\Claude\claude_desktop_config.json`
  1. Add the server configuration:
{
    "mcpServers": {
        "substack": {
            "command": "python",
            "args": [
                "/ABSOLUTE/PATH/TO/substack-mcp-server/substack_mcp.py"
            ]
        }
    }
}
  1. Restart Claude for Desktop

Using with Claude

Once configured, you can ask Claude questions like:

See example queries for more examples.

Available Tools

This MCP server provides the following tools:

Tool Description
get_newsletter_posts Retrieves recent posts from a Substack newsletter
get_post_content Gets the full content of a specific Substack post
search_newsletter Searches for posts within a newsletter
search_across_substacks Searches for content across multiple Substack newsletters
discover_popular_substacks Discovers popular Substack newsletters by category
get_author_info Retrieves information about a Substack author
get_newsletter_recommendations Gets recommended newsletters for a publication
get_newsletter_authors Lists authors of a Substack newsletter

Development

Project Structure

substack-mcp-server/
├── README.md
├── LICENSE
├── requirements.txt
├── Dockerfile
├── substack_mcp.py
└── examples/
    └── example_queries.md

Adding New Tools

To add new tools to the MCP server, add a new function to substack_mcp.py with the @mcp.tool() decorator:

@mcp.tool()
async def my_new_tool(param1: str, param2: int = 5) -> str:
    """
    Description of what the tool does.
    
    Args:
        param1: Description of param1
        param2: Description of param2 (default: 5)
    """
    # Tool implementation
    return "Result"

Cross-Substack Search

The search_across_substacks tool enables powerful research capabilities by searching multiple Substack newsletters simultaneously for specific topics. This allows for:

  • Discovering diverse perspectives on a topic across different authors
  • Comparing coverage of current events across publications
  • Finding the most comprehensive content on niche topics

You can specify which newsletters to search or let the system use a curated list of popular newsletters. Results are organized by newsletter for easy comparison.

Substack Discovery

The discover_popular_substacks tool helps users find new newsletters based on categories of interest. Currently supported categories include:

  • technology
  • politics
  • science
  • culture
  • economics

This feature makes it easier to discover high-quality content creators in specific domains.

Troubleshooting

If you encounter issues:

  1. Check Claude's logs:

    MacOS

tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

# Windows
type %APPDATA%\Claude\Logs\mcp*.log
  1. Ensure your server runs without errors:

    python substack_mcp.py

  2. Verify the configuration file paths in Claude for Desktop.

Contributing

Contributions are welcome! Please feel free to submit a pull request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

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