Price Per TokenPrice Per Token
JFrog MCP Server

JFrog MCP Server

by jfrog

GitHub 110 2 uses
0

About

JFrog MCP Server integrates with the JFrog Platform to provide artifact management, repository operations, and DevOps workflow automation through the Model Context Protocol. Key capabilities include: - Repository Management: Create and configure local, remote, and virtual repositories in Artifactory for package distribution - Build Tracking: List and retrieve build information across your CI/CD pipelines - Artifact Search: Execute AQL (Artifactory Query Language) queries to find artifacts, builds, and packages - Runtime Monitoring: View runtime clusters and monitor running container images - Security Scanning: Access Xray vulnerability data with severity grouping and scan summaries - Package Curation: Check package versions, vulnerabilities, and curation status across your catalog - Mission Control: View and manage associated JFrog Platform instances

README

JFrog MCP Server (🧪 Experimental)

[](https://smithery.ai/server/@jfrog/mcp-jfrog)

Model Context Protocol (MCP) Server for the JFrog Platform API, enabling repository management, build tracking, release lifecycle management, and more.

https://github.com/user-attachments/assets/aca3af2b-f294-41c8-8727-799a019a55b5

Disclaimer

This is an experimental project intended to demonstrate JFrog's capabilities with MCP. It is not officially supported or verified by JFrog.

> Update (2025): JFrog now provides an official, secure, and remotely hosted MCP server for seamless integration with the JFrog Platform. This managed MCP server is maintained by JFrog and is recommended for production use, offering enhanced security, reliability, and support.

Learn more and get started here: 👉 JFrog MCP Server Documentation

Features

  • Repository Management: Create and manage local, remote, and virtual repositories
  • Build Tracking: List and retrieve build information
  • Runtime Monitoring: View runtime clusters and running container images
  • Mission Control: View associated JFrog Platform instances
  • Artifact Search: Execute powerful AQL queries to search for artifacts and builds
  • Catalog and Curation: Access package information, versions, vulnerabilities, and check curation status
  • Xray: Access scan artifacts summary, group by severity per artifact
  • Tools

    Repository Management

    1. check_jfrog_availability - Check if JFrog platform is ready and functioning - Returns: Platform readiness status

    2. create_local_repository - Create a new local repository in Artifactory - Inputs: - key (string): Repository key - rclass (string): Repository class (must be "local") - packageType (string): Package type of the repository - description (optional string): Repository description - projectKey (optional string): Project key to assign the repository to - environments (optional string[]): Environments to assign the repository to - Returns: Created repository details

    3. create_remote_repository - Create a new remote repository in Artifactory to proxy external package registries - Inputs: - key (string): Repository key - rclass (string): Repository class (must be "remote") - packageType (string): Package type of the repository - url (string): URL to the remote repository - username (optional string): Remote repository username - password (optional string): Remote repository password - description (optional string): Repository description - projectKey (optional string): Project key to assign the repository to - environments (optional string[]): Environments to assign the repository to - Many other optional parameters for specific repository configurations - Returns: Created repository details

    4. create_virtual_repository - Create a new virtual repository in Artifactory that aggregates multiple repositories - Inputs: - key (string): Repository key - rclass (string): Repository class (must be "virtual") - packageType (string): Package type of the repository - repositories (string[]): List of repository keys to include in the virtual repository - description (optional string): Repository description - projectKey (optional string): Project key to assign the repository to - environments (optional string[]): Environments to assign the repository to - Other optional parameters for specific repository configurations - Returns: Created repository details

    5. list_repositories - List all repositories in Artifactory with optional filtering - Inputs: - type (optional string): Filter repositories by type (local, remote, virtual, federated, distribution) - packageType (optional string): Filter repositories by package type - project (optional string): Filter repositories by project key - Returns: List of repositories matching the filters

    6. set_folder_property - Set properties on a folder in Artifactory, with optional recursive application - Inputs: - folderPath (string): Path to the folder where properties should be set - properties (object): Key-value pairs of properties to set - recursive (optional boolean): Whether to apply properties recursively to sub-folders - Returns: Operation result

    7. execute_aql_query - Execute an Artifactory Query Language (AQL) query to search for artifacts, builds, or other entities in JFrog Artifactory - Inputs: - query (string): The AQL query to execute. Must follow AQL syntax (e.g., items.find({"repo":"my-repo"}).include("name","path")) - domain (optional string): The primary domain to search in (item

    Related MCP Servers

    AI Research Assistant

    AI Research Assistant

    hamid-vakilzadeh

    AI Research Assistant provides comprehensive access to millions of academic papers through the Semantic Scholar and arXiv databases. This MCP server enables AI coding assistants to perform intelligent literature searches, citation network analysis, and paper content extraction without requiring an API key. Key features include: - Advanced paper search with multi-filter support by year ranges, citation thresholds, field of study, and publication type - Title matching with confidence scoring for finding specific papers - Batch operations supporting up to 500 papers per request - Citation analysis and network exploration for understanding research relationships - Full-text PDF extraction from arXiv and Wiley open-access content (Wiley TDM token required for institutional access) - Rate limits of 100 requests per 5 minutes with options to request higher limits through Semantic Scholar

    Web & Search
    12 8
    Linkup

    Linkup

    LinkupPlatform

    Linkup is a real-time web search and content extraction service that enables AI assistants to search the web and retrieve information from trusted sources. It provides source-backed answers with citations, making it ideal for fact-checking, news gathering, and research tasks. Key features of Linkup: - Real-time web search using natural language queries to find current information, news, and data - Page fetching to extract and read content from any webpage URL - Search depth modes: Standard for direct-answer queries and Deep for complex research across multiple sources - Source-backed results with citations and context from relevant, trustworthy websites - JavaScript rendering support for accessing dynamic content on JavaScript-heavy pages

    Web & Search
    2 24
    Math-MCP

    Math-MCP

    EthanHenrickson

    Math-MCP is a computation server that enables Large Language Models (LLMs) to perform accurate numerical calculations through the Model Context Protocol. It provides precise mathematical operations via a simple API to overcome LLM limitations in arithmetic and statistical reasoning. Key features of Math-MCP: - Basic arithmetic operations: addition, subtraction, multiplication, division, modulo, and bulk summation - Statistical analysis functions: mean, median, mode, minimum, and maximum calculations - Rounding utilities: floor, ceiling, and nearest integer rounding - Trigonometric functions: sine, cosine, tangent, and their inverses with degrees and radians conversion support

    Developer Tools
    22 81