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Skill Retriever
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Skill Retriever

Skill Retriever is an MCP server based on a graph database, specifically designed for the retrieval and installation of Claude Code components. It automatically indexes component repositories on GitHub, returns the minimum correct set of components and their dependencies based on task descriptions through semantic search and graph traversal algorithms, and supports security scanning and automatic synchronization and updates.
Developer toolsArtificial intelligence chatbots#Component Retrieval#Graph Database#Security Scan#Automatic Synchronization.Python
2.5 points
0
Open Site

Overview

Installation

Tools List

Content Details

Alternatives

What is Skill Retriever?

Skill Retriever is an intelligent Claude Code component retrieval system. It solves the problem of fragmented community components - currently, there are more than 2,500 components scattered across 56 GitHub repositories. When you need to complete a specific task, Skill Retriever can intelligently find the most relevant set of components, automatically handle dependencies, and securely install them into your Claude Code environment.

How to use Skill Retriever?

Skill Retriever is integrated into Claude Code as an MCP server. You simply describe your requirements in Claude Code (e.g., 'I need to set up Git commit automation'), and the system will search for relevant components, check dependencies and conflicts, and then install them with one click. The entire process is completed entirely within the Claude Code interface, eliminating the need for manual searching and configuration.

Applicable scenarios

Skill Retriever is particularly suitable for the following scenarios: 1. You need to extend the functionality of Claude Code but don't know which components are available. 2. You need to complete complex tasks involving the collaborative work of multiple components. 3. You're concerned about component compatibility and security issues. 4. You want to automatically keep the component library up - to - date. 5. You need to perform a security scan for potential risks in components.

Main Features

Intelligent Component Retrieval
Combines semantic search and graph relationship analysis to find the most relevant set from 2,561 components. Considers not only content matching but also dependencies between components.
Automatic Dependency Resolution
Automatically identifies and installs all necessary dependent components to ensure that the installed components work properly, avoiding the hassle of manually searching for dependencies.
Security Vulnerability Scanning
Automatically scans components for potential risks based on security research, including 22% of common vulnerability patterns such as data leakage, credential access, and privilege escalation.
Automatic Synchronization and Update
Automatically checks for component library updates every hour to ensure that the components you use are always the latest version. Supports instant updates via GitHub Webhook.
Conflict Detection
Checks for compatibility issues between components before installation to avoid functional conflicts caused by the simultaneous installation of incompatible components.
Learning and Optimization System
The system automatically optimizes the recommendation algorithm based on actual usage. Components that are frequently used together will receive a higher recommendation weight.
LLM - Assisted Security Analysis
Uses the Claude API to conduct in - depth analysis of high - risk components, reducing false positives and providing more accurate security assessments.
Automatic Discovery of New Component Libraries
Regularly discovers new skill repositories from GitHub and automatically indexes them, continuously expanding the available component library.
Advantages
One - stop solution: No need to manually search for components in multiple GitHub repositories.
Intelligent recommendation: Recommends the most suitable component combinations based on task descriptions.
Security guarantee: Built - in security scan to avoid installing risky components.
Automatic maintenance: Components are automatically updated to stay up - to - date.
Easy to use: Fully integrated into Claude Code, no additional tools required.
Time - saving: Automatically handles dependencies and configurations, significantly reducing setup time.
Continuous optimization: The system continuously improves recommendation quality based on usage feedback.
Limitations
Requires a Claude Code environment: Only applicable to Claude Code users.
Network - dependent: Needs access to GitHub to obtain components and updates.
Security scans may produce false positives: Especially bash code examples may be misjudged as risks.
LLM security analysis requires an API key: In - depth security analysis requires configuring the Anthropic API.
Component quality depends on the community: Recommendation quality is affected by the quality of the original components.
New components require time to be indexed: Newly released components may need to wait for the automatic discovery cycle.

How to Use

Configure Claude Code
Add the Skill Retriever MCP server configuration to the Claude Code configuration file.
Restart Claude Code
Restart Claude Code to load the Skill Retriever MCP server.
Describe Your Requirements
Describe the task you need to complete in the Claude Code conversation.
Let Claude Search for Components
Claude will automatically call Skill Retriever to search for relevant components.
View and Confirm Recommendations
View the list of recommended components, including security status and dependencies.
Install Components
After confirming the installation, the components and their dependencies will be automatically installed into the.claude/ directory.

Usage Examples

Automate Git Workflow
The user wants to automate the Git commit process, use a standardized commit message format, and automatically run code checks before committing.
JWT Authentication Setup
Developers need to implement JWT authentication in a project but are unsure which components are available and about security considerations.
Code Review Automation
The team wants to automate the code review process, automatically running code quality, security, and specification checks when a PR is created.
Security Audit of Existing Components
The user has already installed some components and wants to check their security status, especially components obtained from the community.

Frequently Asked Questions

Is Skill Retriever free?
Do I need programming knowledge to use it?
Are the installed components safe?
What if a component doesn't work or has a problem?
How do I update the installed components?
Can I add my own private component library?
Why are some bash codes marked as security risks?
Will Skill Retriever affect the performance of Claude Code?
How do I uninstall unnecessary components?
Which Claude Code versions does Skill Retriever support?

Related Resources

Official GitHub Repository
Source code and latest version of Skill Retriever
Claude Code Documentation
Official usage documentation for Claude Code
Agent Skills Specification
Documentation for the Agent Skills open standard
DeepLearning.AI Agent Skills Course
Official skill - creation course covering the Claude API, Claude Code, and Agent SDK
Anthropic Official Skill Repository
Skill collection maintained by Anthropic officially
MCP Protocol Specification
Official specification documentation for the Model Context Protocol
Security Research Paper
The research 'Agent Skills in the Wild' by Yi Liu et al., on which the Skill Retriever security scan is based

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "skill-retriever": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/skill-retriever", "skill-retriever"]
    }
  }
}

{
     "mcpServers": {
       "skill-retriever": {
         "command": "uv",
         "args": ["run", "--directory", "/path/to/skill-retriever", "skill-retriever"]
       }
     }
   }
Note: Your key is sensitive information, do not share it with anyone.

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