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0xshellming/mcp-summarizer

by Various

MCP Server for AI Summarization

0

MCP

0xshellming/mcp-summarizer

Added 1 June 2026

#ai #ai-summarizer #book #bookreader #deepseek-r1 #ebook #gemini #summarizer

Overview

0xshellming/mcp-summarizer is an MCP (Model Context Protocol) server implemented in JavaScript that provides AI-driven text summarization. It exposes a summarization tool via the MCP protocol, allowing clients to send text and receive concise summaries.

Best for

Best for
Developers who need a straightforward MCP server for text summarization in their AI toolchains

Use cases

  • Add summarization capabilities to MCP-enabled applications
  • Summarize lengthy documents or chat logs in real-time
  • Integrate with MCP-based automation pipelines for content digest

How to use

Install

pnpm install && pnpm run build

Tools exposed

  • summarize
  • greeting

Example client config

{\n  "mcpServers": {\n    "content-summarizer": {\n      "command": "node",\n      "args": [\n        "{ABSOLUTE PATH TO FILE HERE}/dist/index.js"\n      ]\n    }\n  }\n}

Notes

0xshellming/mcp-summarizer is an MCP (Model Context Protocol) server implemented in JavaScript that provides AI-driven text summarization. It exposes a summarization tool via the MCP protocol, allowing clients to send text and receive concise summaries.

161 stars on GitHub. Last updated 2025-02-28.

Use cases

  • Add summarization capabilities to MCP-enabled applications
  • Summarize lengthy documents or chat logs in real-time
  • Integrate with MCP-based automation pipelines for content digest

Pros

  • Lightweight and simple MCP server written in JavaScript
  • Easy to integrate into existing MCP ecosystems
  • Open source with active community (161 stars)

Cons

  • Limited to summarization only; no other NLP features
  • Relies on external AI models or APIs, introducing dependency and potential cost
  • Documentation may be minimal beyond the repository README

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Lightweight and simple MCP server written in JavaScript
  • Easy to integrate into existing MCP ecosystems
  • Open source with active community (161 stars)

Cons

  • Limited to summarization only; no other NLP features
  • Relies on external AI models or APIs, introducing dependency and potential cost
  • Documentation may be minimal beyond the repository README

Pairs with

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