Turn Any Content Into Actionable Summaries in Seconds

Stop manually skimming through lengthy PDFs, web articles, and ebooks to find what matters. This MCP server gives your AI assistant the ability to instantly digest and summarize content from virtually any source—text, URLs, PDFs, EPUBs—using Google's Gemini 1.5 Pro.

The Problem Every Developer Faces

You spend too much time context-switching between reading documentation, research papers, blog posts, and technical articles. Whether you're evaluating a new library, researching solutions, or trying to extract key insights from a 50-page PDF, the manual process kills your flow state.

Most summarization tools force you to copy-paste content, work with limited formats, or produce generic summaries that miss the technical nuances you actually need.

Why This MCP Server Belongs in Your Toolkit

This isn't another basic text summarizer. It's a content processing powerhouse that integrates directly with your MCP-compatible AI assistant:

Multi-Format Intelligence: Process web pages, PDFs, EPUBs, and raw text through a single interface. No more switching between different tools or manual extraction.

Contextual Summarization: Specify exactly what you want to focus on—implementation details, security considerations, performance benchmarks—and get summaries tailored to your needs.

Multi-Language Support: Research doesn't stop at English. Summarize content in multiple languages or get summaries translated to your preferred language.

Flexible Output Styles: Choose between concise overviews, detailed analyses, or bullet-point breakdowns depending on how you process information best.

Real-World Use Cases That Save Hours

API Documentation Deep Dives: Paste a URL to lengthy API docs and get focused summaries of authentication methods, rate limits, and key endpoints without scrolling through marketing fluff.

Research Paper Processing: Upload academic PDFs and extract methodology, key findings, and implementation details in minutes instead of hours.

Technical Blog Analysis: Summarize multiple blog posts about a technology stack to quickly identify common patterns, gotchas, and best practices.

Ebook Chapter Extraction: Process technical ebooks chapter by chapter to build your own condensed reference materials.

Multi-Language Research: Analyze documentation in languages you don't speak fluently—get summaries in English while preserving technical accuracy.

Implementation in Your Workflow

Getting this running takes about 5 minutes:

git clone https://github.com/0xshellming/mcp-summarizer.git
cd mcp-summarizer
pnpm install && pnpm run build && pnpm start

Add it to your MCP client configuration:

{
  "mcpServers": {
    "content-summarizer": {
      "command": "node",
      "args": ["./dist/index.js"]
    }
  }
}

Then start using it immediately:

// Summarize that lengthy architecture blog post
await summarize({
  content: "https://engineering.company.com/how-we-scaled-microservices",
  type: "url",
  maxLength: 300,
  focus: "technical implementation and performance metrics",
  style: "bullet-points"
});

// Process a PDF whitepaper in Chinese, get English summary
await summarize({
  content: base64EncodedPDF,
  type: "pdf",
  language: "en",
  focus: "security vulnerabilities and mitigation strategies",
  style: "detailed"
});

The Integration Advantage

Unlike standalone summarization tools, this MCP server becomes part of your AI assistant's toolkit. Your assistant can automatically summarize content you reference in conversations, process links you share, or analyze documents you upload—all without breaking context or switching applications.

The real power comes from chaining this with other MCP tools. Summarize research, then immediately feed those insights into code generation, documentation writing, or decision-making workflows.

Built with TypeScript and the official MCP SDK, it integrates seamlessly with Claude Desktop, Continue, and other MCP-compatible environments you're already using.

Repository: github.com/0xshellming/mcp-summarizer
Community: 87+ stars, active development
Setup Time: < 5 minutes

Stop spending development time on manual content processing. Add intelligent summarization to your AI toolkit and get back to building.