Overview

The MCP Substack Server bridges the gap between AI assistants and the rich ecosystem of Substack blogs. Substack hosts thousands of independent writers who publish newsletters, articles, and essays that are typically locked behind a simple web page. The server provides a standardized MCP endpoint that allows Claude.ai and other compatible assistants to retrieve, parse, and ingest these posts directly into the assistant’s context. By doing so, developers can treat Substack content as first‑class data sources without building custom scrapers or handling HTML parsing manually.

What Problem Does It Solve?

Many AI workflows require up‑to‑date, domain‑specific knowledge that is only available in niche publications. Substack, being a decentralized platform, lacks an official API for content retrieval. Developers who want to answer questions about recent articles or summarize newsletters often need to write bespoke web‑scraping scripts, manage rate limits, and parse inconsistent HTML structures. The MCP Substack Server abstracts all of this complexity: it accepts a URL, downloads the page, extracts structured metadata (title, author, subtitle) and the main body text, and returns it in a clean format ready for prompt injection or further processing.

Core Functionality

• URL‑to‑Content Translation – A single MCP method () takes a Substack URL and returns a JSON payload containing the post’s title, author, subtitle, and full content.
• Robust Parsing – The server uses reliable parsing logic to handle the common Substack HTML patterns, ensuring that even posts with embedded images or custom styling are rendered correctly.
• Public‑Post Focus – It is designed for public posts, avoiding authentication hurdles and making it safe to expose publicly.
• Claude Desktop Integration – The server is pre‑configured for the Claude desktop app, allowing users to invoke it with natural language prompts such as “Could you download and summarize this Substack post: [URL]?” without additional configuration.

Use Cases & Scenarios

• Content Summarization – Quickly generate executive summaries or bullet‑point highlights of newsletters for busy professionals.
• Knowledge Base Augmentation – Pull recent industry insights into a corporate knowledge base or an internal AI assistant.
• Research Assistance – Automate the retrieval of academic or opinion pieces from Substack for literature reviews.
• Educational Tools – Enable language models to read and explain blog posts in real time, supporting tutoring or learning platforms.

Integration with AI Workflows

The MCP server fits seamlessly into existing AI pipelines. A developer can add the server to their Claude configuration, then reference it in prompts or custom skills. Because MCP follows a uniform request/response schema, downstream components—such as prompt templates, knowledge‑graph builders, or summarization modules—can consume the parsed data without modification. This plug‑and‑play approach reduces development time and keeps the AI’s context tightly coupled to fresh, human‑written content.

Distinct Advantages

• Zero Boilerplate – No need to write or maintain a scraper; the server handles all network and parsing logic.
• Consistency – Structured output guarantees that downstream AI models receive clean, predictable data.
• Open‑Source & MIT Licensed – Developers can inspect or extend the codebase to support private Substack accounts or additional metadata fields.
• Designed for Claude Desktop – Out‑of‑the‑box compatibility means developers can start using Substack content with minimal setup, making it ideal for rapid prototyping or internal tooling.

In summary, the MCP Substack Server empowers AI developers to effortlessly ingest high‑quality blog content into their assistants, unlocking richer knowledge bases and more dynamic interactions without the overhead of custom scraping solutions.