Osv MCP
This project provides a Python - based MCP server for integrating OSV (open - source vulnerability) data with AI assistants or large - language models, and exposes tools and resources through the MCP protocol to enhance the workflows and capabilities of LLMs.
rating : 2 points
downloads : 6
What is the OSV MCP Server?
The OSV MCP Server is an intermediate service that enables AI assistants to query the open - source software vulnerability database (OSV). Through the standardized Model Context Protocol (MCP), AI can obtain the latest security vulnerability information to enhance the accuracy of responses.How to use the OSV MCP Server?
Simply configure the connection information of the AI assistant (such as Claude), and the AI can automatically acquire the vulnerability query capability. Users do not need to operate the server directly, and all interactions are completed through the AI interface.Applicable scenarios
When you need AI to help analyze the security risks of software dependencies, check for known vulnerabilities, or obtain repair suggestions, an AI integrated with the OSV MCP Server can provide professional - level security analysis.Main features
Vulnerability data queryProvides full query capabilities for the OSV database, supporting multi - condition retrieval by software package, version, etc.
Standard protocol integrationAdopts the MCP protocol and is compatible with various AI assistants and large - language models that support this protocol.
Easy deploymentImplemented in Python, with simple dependencies, and can be quickly deployed locally or on a server.
Advantages and limitations
Advantages
Add professional - level security analysis capabilities to AI
Obtain authoritative open - source vulnerability data in real - time
Simple configuration and seamless integration with existing AI workflows
Limitations
Requires the AI assistant to support the MCP protocol
Only provides vulnerability data and does not include automatic generation of repair solutions
Requires simple configuration for first - time use
How to use
Installation preparation
Ensure that Python 3.8+ and the uv package manager are installed on the system.
Get the project code
Clone the repository to the local machine.
Create a virtual environment
Create an independent Python environment for the project to avoid conflicts.
Install dependencies
Install all the Python packages required by the project.
Start the service
Run the server program.
Usage examples
Security audit assistanceWhen developers evaluate the security of project dependencies, they can query known vulnerabilities of specific libraries through AI.
Vulnerability repair decision - makingWhen the security team evaluates the severity of a vulnerability, they can quickly obtain detailed vulnerability information.
Frequently Asked Questions
Which AI assistants support the MCP protocol?
Does it need to be used online?
What is the data update frequency?
Related resources
OSV project official website
Official website of the open - source vulnerability database
MCP protocol description
Technical specification of the Model Context Protocol
uv package manager
Python package management tool used in the project
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