Hypertool MCP

HyperTool is an MCP server management tool that allows the AI to dynamically switch and use toolsets from multiple MCP servers, breaking the tool quantity limit and improving the accuracy and efficiency of AI tool selection through intelligent toolsets.

Developer tools Artificial intelligence chatbots #Tool Management #Dynamic Switching #AI Optimization #MCP Enhancement .TypeScript

rating : 3 points

downloads : 6.5K

update time : 2025-12-12

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What is HyperTool MCP?

HyperTool MCP is an intelligent tool management middleware that solves the problem of too many tools and difficult tool selection when an AI assistant uses multiple MCP tool servers. By creating and managing 'toolsets' (similar to playlists), it allows the AI to only see the tools most relevant to the current task, significantly improving the accuracy and efficiency of tool selection.

How to use HyperTool MCP?

Using HyperTool is very simple: 1) Copy your existing MCP configuration file; 2) Point your AI to the HyperTool server; 3) Create or switch toolsets. Your AI assistant can then seamlessly switch between different toolsets such as 'development mode', 'writing mode', and 'debugging mode'.

Applicable scenarios

HyperTool is particularly suitable for the following scenarios: - Developers use multiple MCP servers (Git, Docker, file system, etc.) for programming. - Content creators need to switch between different workflows such as writing, researching, and publishing. - Teams want to configure dedicated toolsets for different roles (development, testing, operations). - Any user who needs an AI assistant to stay focused in a complex tool environment.

Main Features

Break the tool quantity limit

Connect to an unlimited number of MCP servers and use 10, 50, or even 500+ tools, while your AI will only see the subset of tools most needed for the current task.

Dynamic toolset management

Create, modify, and switch toolsets in real - time. Configure dedicated tool combinations for different tasks (development, writing, debugging) to make the AI focus like an expert.

Pre - configured role packages (new feature)

Use pre - configured MCP server and toolset packages such as 'web - dev', 'data - scientist', etc. to quickly start a specific workflow without configuring from scratch.

Context usage measurement (new feature)

View the estimated token consumption of each tool and optimize the toolset to reduce context occupation, enabling the AI to process important information more efficiently.

Enhanced intelligent tool descriptions

Add examples and context information to tools to help the AI select tools more accurately. According to tests, it can improve the selection accuracy by 89%.

Server group management

Organize related MCP servers into logical groups and start them by project or workflow to keep the environment tidy and focused.

Advantages

Significantly improve the accuracy and efficiency of AI tool selection.

Support unlimited tool expansion, breaking traditional limitations.

Provide ready - to - use role packages, reducing the usage threshold.

Real - time toolset switching to adapt to different work scenarios.

Visualize context usage to help optimize resource configuration.

Limitations

Requires additional configuration steps (but a quick setup wizard is provided).

Some AI clients (such as Claude Desktop) may need to be restarted to switch toolsets.

Pre - configured role packages may not fully meet individual specific needs.

Initial setup requires an understanding of MCP server configuration concepts.

How to Use

Copy the existing configuration

Copy your existing MCP configuration file in the project directory to create a dedicated configuration for HyperTool.

Configure the AI to point to HyperTool

Modify your .mcp.json file to allow the AI client to access all tools through HyperTool.

Create the first toolset

Restart the AI client and then create your first toolset through a conversation.

Switch toolsets (optional)

Let the AI switch to the most suitable toolset according to the current task.

Usage Examples

Development Workflow

When a programmer is developing a feature, they need Git version control, Docker container management, and file system operations. By creating a 'deep - coding' toolset, the AI only sees the 12 most relevant tools instead of all 64 available tools.

Content Creation Workflow

Content creators need to switch between different platforms and tools. Through the 'writing' toolset, the AI can access Notion documents, Slack messages, and grammar checking tools and focus on the writing task.

Quick Start for Web Development

New users who don't want to manually configure all MCP servers can directly use the pre - configured 'web - dev' role package to immediately get a complete Web development tool environment.