H

Humanmcp

HumanMCP is a manually operated MCP server project where users need to manually read requests and write responses.
2.5 points
12

What is HumanMCP?

HumanMCP is a unique MCP server implementation where all request processing is done manually by a human operator. Instead of automated responses, you read requests from a file and write responses to another file.

How to use HumanMCP?

After setting up the server, you monitor incoming requests in 'in.txt' and manually craft responses in 'out.txt'. This gives you complete control over every interaction.

Use Cases

Ideal for debugging complex MCP interactions, testing client behavior, or educational purposes where you want to understand the protocol deeply.

Key Features

Complete Manual ControlEvery request and response is handled manually by the operator
Simple Text InterfaceUses simple text files (in.txt/out.txt) for communication
Protocol Learning ToolGreat for understanding MCP protocol details

Pros and Cons

Advantages
Complete control over every response
Excellent for debugging and testing
Simple setup with minimal dependencies
Limitations
Not suitable for production use
Requires constant manual intervention
Slower than automated servers

Getting Started

Download the server
Get the latest release from GitHub
Configure your MCP client
Add the server to your MCP host settings
Monitor requests
Watch for incoming requests in in.txt
Send responses
Write your responses to out.txt

Example Scenarios

Initial SetupResponding to client initialization
Weather ForecastResponding to a weather query

Frequently Asked Questions

Is this server suitable for production use?
How do I handle multiple concurrent requests?
Can I automate parts of the response process?

Additional Resources

GitHub Repository
Source code and releases
MCP Protocol Documentation
Official protocol specifications
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
Featured MCP Services
G
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
100
4.3 points
M
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
1.7K
5 points
N
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
153
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
840
4.3 points
U
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#
575
5 points
F
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
6.7K
4.5 points
C
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
5.2K
4.7 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
761
4.8 points
AIbase
Zhiqi Future, Your AI Solution Think Tank
© 2025AIbase