MCP Summarization Functions
An MCP server that provides intelligent text summarization functions for AI agents, optimizing context window management and improving AI work efficiency
rating : 2.5 points
downloads : 6.6K
What is the MCP Summary Function Server?
The MCP Summary Function Server is a powerful tool that helps AI assistants work more efficiently by generating concise and useful summaries through executing commands, analyzing files and directories, etc.How to use the MCP Summary Function Server?
Simply configure the server and call the corresponding API to generate the required summaries.Applicable Scenarios
It is suitable for situations where you need to quickly understand complex data or command outputs, such as file system analysis and API response processing.Main Features
Command Output Summary
Execute commands and generate concise result summaries.
File Content Analysis
Summarize one or more files while maintaining technical accuracy.
Directory Structure Overview
Provide a clear view of complex directory structures.
Arbitrary Text Summary
Generate summaries for any input text.
Advantages
Reduce context overflow and improve the efficiency of AI assistants
Generate focused analysis and enhance response quality
Optimize resource usage and reduce operating costs
Limitations
Rely on external APIs, which may incur additional costs
For very large datasets, the summaries may not be detailed enough
How to Use
Install the Server
Install the server via npm or add the server to your MCP configuration file.
Configure Environment Variables
Set necessary environment variables such as API keys and model IDs.
Call the API
Use the provided function interfaces to generate summaries.
Usage Examples
Example 1: Command Output Summary
Generate a summary of the Git commit history.
Example 2: File Content Analysis
Analyze the key configuration files in the project.
Frequently Asked Questions
How to choose the appropriate model?
Will the summary affect the integrity of the original data?
Related Resources
Official Documentation
Detailed installation and usage guides.
GitHub Repository
Source code and contribution guides.

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
17.5K
4.5 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
28.6K
5 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
17.5K
4.3 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
53.9K
4.3 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
51.3K
4.5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
24.3K
5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
17.2K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
75.7K
4.7 points

