Tiger Skills MCP Server
Tiger Skills MCP Server is a server based on the Model Context Protocol (MCP), aiming to enhance the professional capabilities of AI agents through modular skills (Skills). It supports the configuration of local and GitHub skill libraries and provides sub - agent task execution functions.
rating : 2.5 points
downloads : 0
What is Tiger Skills MCP Server?
Tiger Skills MCP Server is a middleware server that implements the Model Context Protocol (MCP) standard and provides a modular skill system for AI agents. Skills are like 'professional toolkits' installed on AI agents, and each skill contains knowledge, workflows, and tools in a specific domain. For example, a 'financial modeling' skill can enable an AI agent to understand financial formulas and report structures, while a 'front - end design' skill can allow it to generate compliant web code.How to use Tiger Skills MCP Server?
Using Tiger Skills MCP Server mainly consists of three steps: 1) Configure the skill collection and specify the skills to be loaded through a YAML file (it can be a local folder or a GitHub repository); 2) Start the MCP server, which can be run via HTTP or standard input/output; 3) Connect to the server in an MCP - supported client (such as Claude Desktop), and the AI agent can automatically recognize and use the configured skills.Applicable scenarios
Tiger Skills MCP Server is particularly suitable for the following scenarios: Enterprises need to add company - specific workflows and knowledge bases to AI assistants; Development teams want AI assistants to understand their code specifications and architectures; Educational institutions want to create AI tutoring assistants for specific disciplines; Individual users want to expand the capabilities of AI assistants to handle repetitive professional tasks.Main features
Skill management
Supports loading skill collections from local directories or GitHub repositories. Specific skills can be flexibly enabled or disabled to ensure that AI agents only use relevant professional knowledge.
Standardized skill structure
Fully compatible with Anthropic's skill specification. Each skill contains a necessary SKILL.md file and optional scripts, reference materials, and resource files to ensure the quality and consistency of skills.
Sub - agent task execution
Provides a subagent tool that can decompose complex tasks into multiple subtasks, which are handled by independent agent instances. It is particularly suitable for workflows that require processing large amounts of data or multiple steps.
Progressive information loading
Adopts a three - layer loading system: Metadata is always in the context, the skill body is loaded when triggered, and resource files are loaded on demand to optimize the use efficiency of the context window.
Multiple transport protocols
Supports two connection methods, HTTP and STDIO, for easy integration in different environments, including local development, Claude Desktop, and web applications.
Advantages
Modular design: Skills can be independently developed, tested, and deployed for easy maintenance and updates.
Resource - efficient: The progressive loading mechanism avoids unnecessary context occupation and improves processing efficiency.
Flexible configuration: Supports enabling/disabling skills on demand to adapt to different usage scenarios and requirements.
Community - compatible: Follows the Anthropic skill specification and can reuse the existing skill ecosystem.
Easy to integrate: Provides clear configuration examples and multiple connection methods to reduce integration difficulty.
Limitations
Learning curve: Understanding the MCP protocol and skill specification is required to effectively create custom skills.
External dependency: GitHub skills require a valid GitHub Token and network connection.
Configuration complexity: YAML configuration files and environment variable settings may be complex for non - technical users.
Performance consideration: Loading a large number of skills or large resource files may affect the response speed.
Platform dependency: Some functions (such as sub - agents) require specific client support.
How to use
Environment preparation
Install the Node.js and bun runtimes, clone the project repository, and install the dependency packages.
Configure GitHub Token
Create a GitHub Token (requires repo, read:org, read:user, user:email permissions), create a.env file in the project root directory, and set GITHUB_TOKEN.
Configure the skill collection
Create or modify the configuration file to specify the source of the skills to be loaded. Local and GitHub skills can be used in combination.
Start the server
Choose the HTTP or STDIO method to start the server. The HTTP method is suitable for web integration, and the STDIO method is suitable for Claude Desktop.
Client connection
Configure the server connection in an MCP - supported client. For Claude Desktop, edit the configuration file to add MCP server settings.
Usage examples
Enterprise knowledge base integration
A company wants their AI assistant to understand the company's internal processes, document templates, and business rules. They created a set of company - specific skills, including financial report templates, contract review guidelines, and project management system integration.
Development team code specification
A development team wants the AI assistant to follow the team's coding specifications, architectural patterns, and testing requirements when writing code. They created skills such as front - end development, back - end API design, and database migration.
Professional tutoring in the education field
A university wants to create an AI tutoring assistant to help students solve problems in specific disciplines. They developed skills such as mathematical problem - solving, physical experiment design, and literary analysis.
Frequently Asked Questions
What is MCP (Model Context Protocol)?
What is the difference between skills and tools?
Do I need programming knowledge to create skills?
What if the skill file is too large? Will it affect performance?
Can I use Tiger Skills MCP Server in a production environment?
How to debug the problem that a skill does not work?
Related resources
Official documentation of the Model Context Protocol
The complete technical specification and introduction of the MCP protocol.
Anthropic skill specification
Detailed specifications and requirements for the skill format.
Tiger Skills MCP Server code repository
The source code and latest updates of the project.
Official Anthropic skill examples
A collection of skill examples provided by Anthropic for learning reference.
Claude Desktop configuration guide
How to configure the MCP server in Claude Desktop.

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