JVM MCP Server - Alternatives & Competitors

Ranked by Relevance

• 1
  

  VictoriaMetrics MCP Server

  Model Context Protocol server enabling advanced monitoring and observability for VictoriaMetrics.

  VictoriaMetrics MCP Server implements the Model Context Protocol (MCP) to provide seamless integration with VictoriaMetrics, allowing advanced monitoring, data exploration, and observability. It offers access to almost all read-only APIs, as well as embedded documentation for offline usage. The server facilitates comprehensive metric querying, cardinality analysis, alert and rule testing, and automation capabilities for engineers and tools.

  87 11 MCP
• 2
  

  Maven Tools MCP Server

  Universal Maven Central dependency intelligence server for JVM build tools via the Model Context Protocol.

  Maven Tools MCP Server provides an MCP-compliant API delivering rich Maven Central dependency intelligence for JVM build tools like Maven, Gradle, SBT, and Mill. It enables AI assistants to instantly analyze, interpret, and recommend updates, health checks, and maintenance insights by reading maven-metadata.xml directly from Maven Central. With Context7 integration, it supports orchestration and documentation, enabling bulk analysis, stable version filtering, risk assessment, and rapid cached responses. Designed for seamless integration into AI workflows via the Model Context Protocol.

  14 2 MCP
• 3
  

  Last9 MCP Server

  Enables AI agents to access real-time production observability data for automated code fixes.

  Last9 MCP Server is an implementation of the Model Context Protocol (MCP) designed to provide seamless integration between AI agents and production observability data. It allows tools and agents to fetch live logs, metrics, traces, events, and alerts from Last9 systems, supporting a range of development environments and IDEs. This enables faster debugging, automated code fixes, and insightful context directly within local development workflows.

  46 8 MCP
• 4
  

  MCP System Monitor

  Real-time system metrics for LLMs via Model Context Protocol

  MCP System Monitor exposes real-time system metrics, such as CPU, memory, disk, network, host, and process information, through an interface compatible with the Model Context Protocol (MCP). The tool enables language models to retrieve detailed system data in a standardized way. It supports querying various hardware and OS statistics via structured tools and parameters. Designed with LLM integration in mind, it facilitates context-aware system monitoring for AI-driven applications.

  73 17 MCP
• 5
  

  Mifos MCP - Model Context Protocol (MCP)

  Enabling AI agents to access and operate on financial data in the Mifos X ecosystem using Model Context Protocol.

  Mifos MCP provides a Model Context Protocol (MCP) interface tailored for the Mifos X ecosystem, empowering AI agents to interact with financial data and perform operations within the platform. It offers a Java (Quarkus) implementation, with easy configurability via environment variables and native executable support. Developers can test and debug deployments with the MCP Inspector, and detailed instructions ensure smooth setup and integration. Comprehensive examples demonstrate practical banking and financial automation workflows.

  17 12 MCP
• 6
  

  Vibe Check MCP

  Plug & play agent oversight tool to keep LLMs aligned, reflective, and safe.

  Vibe Check MCP provides a mentor layer over large language model agents to prevent over-engineering and promote optimal, minimal pathways. Leveraging research-backed oversight, it integrates seamlessly as an MCP server with support for STDIO and streamable HTTP transport. The platform enhances agent reliability, improves task success rates, and significantly reduces harmful actions. Designed for easy plug-and-play with MCP-aware clients, it is trusted across multiple MCP platforms and registries.

  315 36 MCP
• 7
  

  Inspektor Gadget MCP Server

  AI-powered Kubernetes troubleshooting via Model Context Protocol.

  Inspektor Gadget MCP Server provides an AI-powered debugging and inspection interface for Kubernetes clusters. Leveraging the Model Context Protocol, it enables intelligent output summarization, one-click deployment of Inspektor Gadget, and automated discovery of debugging tools from Artifact Hub. The server integrates seamlessly with VS Code for interactive AI commands, simplifying Kubernetes troubleshooting and monitoring workflows.

  16 1 MCP
• 8
  

  Jupyter MCP Server

  Real-time, context-aware MCP server for managing and interacting with Jupyter Notebooks.

  Jupyter MCP Server is an implementation of the Model Context Protocol (MCP) designed to enable AI-driven, real-time management and interaction with Jupyter Notebooks. It offers context-aware capabilities, smart execution features, and multimodal output handling, seamlessly integrating with JupyterLab and supporting multiple notebooks simultaneously. The server is compatible with any MCP client and can work with local or hosted Jupyter deployments.

  765 127 MCP
• 9
  

  ScreenMonitorMCP v2

  Real-time screen monitoring and visual analysis for AI assistants via MCP.

  ScreenMonitorMCP v2 is a Model Context Protocol (MCP) server enabling AI assistants to capture, analyze, and interact with screen content in real time. It supports instant screenshots, live streaming, advanced vision-based analysis, and provides performance monitoring across Windows, macOS, and Linux. Integration with clients like Claude Desktop is streamlined, offering easy configuration and broad compatibility. The tool leverages AI vision models to provide intelligent insights into screen content and system health.

  64 14 MCP
• 10
  

  JADX-AI-MCP

  Automated AI-powered APK analysis via Model Context Protocol.

  JADX-AI-MCP is a fully automated server and plugin for integrating Model Context Protocol (MCP) with JADX for the purpose of analyzing Android APKs using large language models such as Claude. It streamlines vulnerability discovery, reverse engineering, and static analysis by leveraging LLMs in conjunction with established tools. The project facilitates real-time code review and efficient collaboration between AI and human analysts.

  637 72 MCP
• 11
  

  OPC UA MCP Server

  Bridge AI agents with OPC UA industrial systems in real time.

  OPC UA MCP Server enables seamless integration of AI agents with OPC UA-enabled industrial automation systems. It provides real-time monitoring, analysis, and control of operational data through a set of standardized tool APIs. Supporting both reading and writing of OPC UA nodes, the server facilitates natural language interaction by exposing tools for AI-driven automation and control workflows.

  20 8 MCP
• 12
  

  Modbus MCP Server

  Standardizes Modbus data for seamless AI integration via the Model Context Protocol.

  Modbus MCP Server provides an MCP-compliant interface that standardizes and contextualizes Modbus device data for use with AI agents and industrial IoT systems. It supports flexible Modbus connections over TCP, UDP, or serial interfaces and offers a range of Modbus tools for reading and writing registers and coils. With customizable prompts and structured tool definitions, it enables natural language-driven interactions and analysis of Modbus data within AI workflows. The solution is designed to ensure interoperability and easy configuration within MCP-compatible environments.

  18 7 MCP
• 13
  

  SafeDep VET

  Enterprise-grade open source software supply chain security with MCP capabilities.

  SafeDep VET is an open source tool that provides supply chain security for open source software, featuring advanced software composition analysis and policy-as-code driven security enforcement. It supports multiple package ecosystems and integrates with CI/CD pipelines. Notably, it offers an MCP (Model Context Protocol) server mode to vet open source packages arising from AI-suggested code, and includes agent-based querying and scan result analysis powered by AI. The tool enables real-time malicious package detection through cloud integration and prioritizes actionable insights by analyzing actual code usage.

  829 68 MCP
• 14
  

  MCP Server for Data Exploration

  Interactive Data Exploration and Analysis via Model Context Protocol

  MCP Server for Data Exploration enables users to interactively explore and analyze complex datasets using prompt templates and tools within the Model Context Protocol ecosystem. Designed as a personal Data Scientist assistant, it facilitates the conversion of raw data into actionable insights without manual intervention. Users can load CSV datasets, run Python scripts, and generate tailored reports and visualizations through an AI-powered interface. The server integrates directly with Claude Desktop, supporting rapid setup and seamless usage for both macOS and Windows.

  503 63 MCP
• 15
  

  mcp-log-proxy

  Web-based proxy for inspecting Model Context Protocol traffic in real time.

  mcp-log-proxy enables users to observe and debug messages exchanged between MCP clients and servers through a user-friendly web interface. It supports the STDIO interface and can operate multiple proxy instances, each accessible via a web dashboard. The tool allows customization of ports, web page titles, and log file locations, making it suitable for managing and troubleshooting MCP-based model communication. Installation is straightforward via Homebrew or Go, and it supports real-time switching between different running proxies.

  26 3 MCP
• 16
  

  MCPR

  Stateful Human-AI Collaboration and Persistent R Sessions

  MCPR enables AI agents to establish interactive, persistent sessions within a live R environment, allowing for stateful, multi-step analytical workflows. By leveraging JSON-RPC 2.0 over `nanonext` sockets, it facilitates robust, asynchronous communication and exposes R session functionalities as modular tools. The framework includes session management, service discovery, and advanced plot rendering capabilities, making it ideal for collaborative and iterative data analysis.

  16 5 MCP
• 17
  

  Chargebee AgentKit MCP Server

  Integrate Chargebee into AI agents for intelligent billing and subscription workflows.

  Chargebee AgentKit provides a toolkit to enhance AI applications with Chargebee’s billing and subscription management capabilities. It includes an MCP Server enabling seamless integration with AI-powered code editors such as Cursor, Windsurf, and Cline, and tools like Claude Desktop. The solution allows users to simplify and automate billing processes within agentic AI systems. Designed for developers, it boosts productivity and streamlines subscription workflows.

  13 7 MCP
• 18
  

  MCP Server for ZenML

  Expose ZenML data and pipeline operations via the Model Context Protocol.

  Implements a Model Context Protocol (MCP) server for interfacing with the ZenML API, enabling standardized access to ZenML resources for AI applications. Provides tools for reading data about users, stacks, pipelines, runs, and artifacts, as well as triggering new pipeline runs if templates are available. Includes robust testing, automated quality checks, and supports secure connection from compatible MCP clients. Designed for easy integration with ZenML instances, supporting both local and remote ZenML deployments.

  32 10 MCP
• 19
  

  Octagon Deep Research MCP

  AI-powered, enterprise-grade deep research server for MCP clients.

  Octagon Deep Research MCP provides specialized AI-driven research and analysis via seamless integration with MCP-enabled applications. It offers comprehensive multi-source data aggregation, advanced analysis tools, and generates in-depth reports across various domains. The solution emphasizes high performance with no rate limits, enterprise-grade speed, and universal compatibility for teams needing thorough research capabilities.

  70 12 MCP
• 20
  

  mcp_vms

  MCP-compliant server for seamless VMS (CCTV) integration and video access.

  mcp_vms implements an MCP server that bridges CCTV Video Management Systems (VMS) with model context protocols. It retrieves live and recorded video streams, exposes channel information and status, and supports remote video playback control and PTZ camera management. Comprehensive error handling and logging ensure reliable integration with AI tooling requiring contextual video feeds.

  11 3 MCP
• 21
  

  Optuna MCP Server

  Automated model optimization and analysis via the Model Context Protocol using Optuna.

  Optuna MCP Server is an implementation of the Model Context Protocol (MCP) that enables automated hyperparameter optimization and analysis workflows through Optuna. It acts as a server providing standardized tools and endpoints for creating studies, managing trials, and visualizing optimization results. The server facilitates integration with MCP clients and supports deployment via both Python environments and Docker. It streamlines study creation, metric management, and result handling using Optuna’s capabilities.

  65 21 MCP
• 22
  

  Zaturn

  Your Co-Pilot For Data Analytics & Business Insights

  Zaturn enables AI models to interact with multiple data sources and generate analytics without requiring users to write SQL or Python code. It supports SQL databases and file formats, providing visual and tabular summaries and offering an interactive web interface similar to Jupyter Notebook. Zaturn can function both as a standalone platform or as a Model Context Protocol (MCP) compliant tool, allowing seamless context management for AI-driven data analysis.

  66 9 MCP
• 23
  

  Creatify MCP Server

  MCP server bringing Creatify AI's advanced video generation to every AI assistant.

  Creatify MCP Server is a comprehensive Model Context Protocol (MCP) server that integrates Creatify AI's video generation platform with AI assistants, chatbots, and automation tools. It provides advanced capabilities such as natural language video creation prompts, progress tracking, structured logging, and reusable workflows through a standardized MCP interface. Built with TypeScript and leveraging the Creatify API, it exposes a wide range of powerful video generation and editing actions that can be controlled programmatically.

  14 3 MCP
• 24
  

  AutoMobile

  Powerful tools for mobile automation, test authoring, and device management via MCP.

  AutoMobile provides a comprehensive set of tools for mobile automation, focusing on UI testing and development workflow automation. It operates as an MCP Server, enabling a robust interaction loop for model-driven actions and observations. The solution supports Android platforms with features like automated test authoring, multi-device management, and seamless CI test execution. AutoMobile also offers source mapping and deep view hierarchy analysis to enhance code rendering accuracy.

  63 8 MCP
• 25
  

  Webpage Screenshot MCP Server

  Capture web page screenshots programmatically for AI agent workflows.

  Webpage Screenshot MCP Server enables the capture of webpage and element screenshots using Puppeteer, providing a Model Context Protocol-compliant interface for AI agents. It supports various image formats, flexible authentication, and session persistence to facilitate integration with tools like Claude and Cursor. The server simplifies visual verification and monitoring of web applications by returning base64-encoded screenshots through customizable options. It also allows manual login workflows and multi-step web interactions with session continuity.

  44 4 MCP
• 26
  

  Crypto-Pegmon-MCP

  Cross-chain stablecoin peg monitoring and stability reporting MCP server.

  Crypto-Pegmon-MCP is an MCP-compatible server that monitors stablecoin peg integrity across multiple blockchains. It provides AI agents with real-time and historical data on peg stability for 17 USD-pegged stablecoins. The server generates stability reports and presents data in Markdown format, facilitating easy integration into dashboards or automated agent workflows. Users can query supported coins, current prices, and analyze historical deviations to assess depegging risks.

  4 6 MCP
• 27
  

  MCP Internet Speed Test

  Standardized internet speed and network performance testing for AI models via MCP.

  MCP Internet Speed Test implements the Model Context Protocol (MCP) to enable AI models and agents to measure, analyze, and report diverse network performance metrics through a standardized interface. It supports download, upload, latency, jitter, and cache analysis, along with multi-CDN and geographic location detection. By offering an MCP-compatible server with robust testing features, it allows seamless integration with LLMs and AI tools for real-time network assessment and diagnostics.

  11 7 MCP
• 28
  

  Smart Tree

  Lightning Fast Directory Visualization and AI-Enabled Context Compression.

  Smart Tree is a high-performance directory visualization tool built with Rust, offering advanced context management and AI-integrated features. It supports persistent memory anchoring, compressed context formats for reduced token usage, and real-time, interactive terminal UI via Spicy TUI mode. The tool provides programmatic hooks for MCP compliance, enabling AI assistants to recall and leverage project insights efficiently.

  175 15 MCP
• 29
  

  Token Revoke MCP

  Securely manage and revoke ERC-20 token allowances across multiple EVM chains

  Token Revoke MCP is a Model Context Protocol (MCP) server designed to enhance security by allowing users to check and revoke ERC-20 token allowances on over 50 EVM-compatible chains. It provides endpoints to fetch token approval data for wallets, submit revocation transactions, and check transaction statuses. The service leverages the Moralis API for blockchain data and supports natural language interactions for ease of use. It is intended to give users granular control over their token approvals and exposure.

  2 6 MCP
• 30
  

  MacOS Resource Monitor MCP Server

  Lightweight MCP server for monitoring CPU, memory, and network usage on macOS.

  MacOS Resource Monitor MCP Server provides real-time monitoring of system resources on macOS devices, exposing an MCP endpoint for integration with LLMs or other clients. It identifies resource-intensive processes across CPU, memory, and network, delivering structured JSON outputs. The server offers advanced filtering, sorting, and system overviews, assisting in performance analysis and bottleneck identification. Designed for seamless integration and lightweight system monitoring.

  16 3 MCP
• 31
  

  Aibolit MCP Server

  MCP server providing critical design feedback for Java code analysis.

  Aibolit MCP Server acts as a bridge between AI code assistants and the Aibolit Java code analyzer, delivering assessments of the most critical design issues in a codebase. It integrates with agents such as Claude Code to help prioritize significant refactoring tasks over minor, cosmetic changes. The tool supports Node.js environments and leverages the Aibolit analysis engine to guide AI agents in making informed, impactful code improvements.

  20 5 MCP
• 32
  

  VictoriaLogs MCP Server

  MCP server enabling advanced read-only access and observability for VictoriaLogs

  VictoriaLogs MCP Server implements the Model Context Protocol (MCP) to provide seamless, read-only integration with VictoriaLogs instances. It enables comprehensive access to VictoriaLogs APIs, allowing for log querying, exploration, and advanced observability tasks. The server includes embedded and searchable documentation and supports automation and interaction capabilities via standardized MCP tools. Designed to combine with other MCP servers, it enhances engineering workflows for log analysis and troubleshooting.

  30 7 MCP
• 33
  

  JMeter MCP Server

  Execute and analyze JMeter tests via Model Context Protocol integration.

  JMeter MCP Server enables execution and analysis of Apache JMeter tests through MCP-compatible clients. It provides command-line and programmatic tools for running JMeter tests in GUI and non-GUI modes, parsing and analyzing JTL result files, and generating detailed metrics and reports. Designed for integration with tools that follow the Model Context Protocol, it facilitates seamless performance testing workflows and actionable insights for test results.

  47 16 MCP
• 34
  

  1mcp-app/agent

  A unified server that aggregates and manages multiple Model Context Protocol servers.

  1MCP Agent provides a single, unified interface that aggregates multiple Model Context Protocol (MCP) servers, enabling seamless integration and management of external tools for AI assistants. It acts as a proxy, managing server configuration, authentication, health monitoring, and dynamic server control with features like asynchronous loading, tag-based filtering, and advanced security options. Compatible with popular AI development environments, it simplifies setup by reducing redundant server instances and resource usage. Users can configure, monitor, and scale model tool integrations across various AI clients through easy CLI commands or Docker deployment.

  96 14 MCP
• 35
  

  MCP GitLab Jira Server

  MCP server for seamless GitLab and Jira integration

  MCP GitLab Jira Server acts as a bridge, enabling AI agents to interact programmatically with GitLab and Jira instances via the Model Context Protocol. It provides a standardized server interface for operations on projects, merge requests, pipelines, branches, issues, releases, and users in GitLab, as well as tickets and project management features in Jira. The server can be run as a CLI tool or in a Docker container, making it compatible with tools like gemini-cli. Configuration via environment variables allows secure authentication and flexible deployment.

  6 4 MCP
• 36
  

  CockroachDB MCP Server

  Natural language interface for managing CockroachDB via MCP protocol

  CockroachDB MCP Server enables natural language interactions with CockroachDB, integrating with Model Context Protocol (MCP) clients. It supports comprehensive database management, cluster monitoring, and SQL operations through standardized tools. Designed for LLMs and agentic applications, it facilitates seamless AI-driven workflows to query, manipulate, and monitor CockroachDB databases. The system emphasizes performance, scalability, and easy integration with popular LLM tools.

  6 3 MCP
• 37
  

  Quarkus Model Context Protocol Servers

  Extensible Java-based servers implementing the Model Context Protocol for context-aware LLM integrations.

  Quarkus Model Context Protocol Servers offers a collection of Java-based servers implementing the Model Context Protocol (MCP) to extend the capabilities of language model applications. Built with the Quarkus MCP server framework, it enables integration with JDBC databases, JVM processes, file systems, JavaFX, Kubernetes, containers, and Wolfram Alpha. The project allows easy deployment and extension of context-aware services for AI applications via MCP. Its servers can be run across different environments using jbang and are easily extensible for new capabilities.

  176 46 MCP
• 38
  

  Agent-MCP

  Multi-Agent Collaboration Protocol for Coordinated AI Software Development

  Agent-MCP enables advanced multi-agent orchestration for AI-driven software development, allowing specialized agents to collaborate via a shared persistent context. Its system manages parallel execution, persistent memory graphs, and real-time task coordination with robust visualization tools. Designed for experienced developers, it features intelligent task management and conflict prevention for scalable and complex codebases. The protocol emphasizes maintaining and sharing context among agents through standardized mechanisms.

  1,021 124 MCP
• 39
  

  Discord MCP

  Seamlessly integrate AI and Discord through the Model Context Protocol.

  Discord MCP is a server implementing the Model Context Protocol (MCP) for the Discord API using JDA, enabling AI assistants and applications to interact with Discord servers. It facilitates the management of channels, messages, and server information, supporting automation and integration with MCP-compatible clients such as Claude Desktop. Installation is supported via Docker and manual builds with Maven, providing flexibility for deployment. It enables enhanced automation and context management for Discord bots via the standardized MCP interface.

  116 23 MCP
• 40
  

  MCP K8S Go

  Golang-based MCP server that enables AI-driven interactions with Kubernetes clusters.

  MCP K8S Go provides a server implementation of the Model Context Protocol for managing and interacting with Kubernetes clusters. It offers functionality to list, retrieve, create, and modify Kubernetes resources such as contexts, namespaces, pods, and nodes using standardized context-aware approaches. Designed for integration with AI assistants like Claude Desktop, it enables prompting and tool execution to manage cluster state, monitor events, fetch pod logs, and run in-pod commands. The solution supports deployment via various installation methods including Docker, Node.js, and Go binaries.

  356 50 MCP
• 41
  

  codelogic-mcp-server

  Leverage CodeLogic’s dependency data for AI-powered impact analysis.

  Codelogic-mcp-server implements an MCP (Model Context Protocol) server, enabling integration of CodeLogic's software dependency data into AI programming assistants. It provides tools for code and database impact assessments by interacting with a CodeLogic server, enhancing context-aware code and database analysis. The server supports integration with popular IDEs, including VS Code and Claude Desktop, using Astral UV/UVX for communication. This solution is designed to bring actionable dependency insights to AI coding workflows.

  31 14 MCP
• 42
  

  MCP Language Server

  Bridge codebase navigation tools to AI models using MCP-enabled language servers.

  MCP Language Server implements the Model Context Protocol, allowing MCP-enabled clients, such as LLMs, to interact with language servers for codebase navigation. It exposes standard language server features—like go to definition, references, rename, and diagnostics—over MCP for seamless integration with AI tooling. The server supports multiple languages by serving as a proxy to underlying language servers, including gopls, rust-analyzer, and pyright.

  1,256 94 MCP
• 43
  

  OpenLink MCP Server for JDBC

  A lightweight Java-based MCP server enabling model context protocol integration with any JDBC-compatible database.

  OpenLink MCP Server for JDBC provides a Java-based implementation of the Model Context Protocol (MCP), facilitating structured, context-aware interactions with relational databases via JDBC. It supports a variety of database operations, including schema and table discovery, table element descriptions, SQL query execution in multiple formats, and Virtuoso-specific features. Easily configurable and designed for integration with tools like Claude Desktop, it enables model-context-aware applications to access and manage database content effectively.

  8 7 MCP
• 44
  

  mcp-k8s-eye

  Kubernetes management and diagnostics tool with MCP protocol support.

  mcp-k8s-eye enables users to manage and analyze Kubernetes clusters using standardized Model Context Protocol (MCP) interfaces. It offers comprehensive resource operations, diagnostics, and resource usage monitoring through both stdio and SSE transports. Supporting generic and custom resource management along with advanced diagnostic tooling, it is geared for integration with AI clients and other MCP consumers.

  26 9 MCP
• 45
  

  Druid MCP Server

  Comprehensive Model Context Protocol server for advanced Apache Druid management and analytics

  Druid MCP Server provides a fully MCP-compliant interface for managing, analyzing, and interacting with Apache Druid clusters. Leveraging tools, resources, and AI-assisted prompts, it enables LLM clients and AI agents to perform operations such as time series analysis, statistical exploration, and data management through standardized protocols. The server is built with a feature-based architecture, offers real-time communication via multiple transports, and includes automatic discovery and registration of MCP components.

  9 4 MCP
• 46
  

  Aiven MCP Server

  Model Context Protocol server enabling LLMs to access and manage Aiven cloud data services.

  Aiven MCP Server implements the Model Context Protocol (MCP) to provide secure access to Aiven's PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch services. It enables Large Language Models (LLMs) to seamlessly integrate and interact with these cloud data platforms, supporting full stack solution development. The server offers streamlined tools for project and service management via standardized APIs and supports integration with platforms like Claude Desktop and Cursor. Environment variable configuration and explicit permission controls are used to ensure secure and flexible operations.

  11 11 MCP
• 47
  

  OpsLevel MCP Server

  Read-only MCP server for integrating OpsLevel data with AI tools.

  OpsLevel MCP Server implements the Model Context Protocol to provide AI tools with a secure way to access and interact with OpsLevel account data. It supports read-only operations for a wide range of OpsLevel resources such as actions, campaigns, checks, components, documentation, domains, and more. The tool is compatible with popular environments including Claude Desktop and VS Code, enabling easy integration via configuration and API tokens. Installation options include Homebrew, Docker, and standalone binaries.

  8 7 MCP
• 48
  

  mcp-server-atlassian-jira

  Seamlessly connect AI assistants to Jira for project and issue management via Model Context Protocol.

  Enables AI assistants like Claude and Cursor to interact directly with Atlassian Jira projects, issues, and workflows using the Model Context Protocol (MCP). Provides standardized context and actions such as querying project status, searching issues, and managing comments through a command-line MCP server. Designed for integration with multiple AI tools, allowing natural language project interaction and instant workflow insights.

  39 16 MCP
• 49
  

  Kubectl MCP Server

  Natural language Kubernetes management for AI assistants using the Model Context Protocol.

  Kubectl MCP Server enables AI assistants such as Claude and Cursor to interact with Kubernetes clusters using natural language through the Model Context Protocol (MCP). It supports a wide range of Kubernetes operations including resource management, Helm integration, monitoring, diagnostics, and advanced security features. The server is designed to handle context-aware commands, maintain session memory, and provide intelligent command construction and explanations. Integration with multiple AI assistants and flexible transport protocols are supported for a seamless user experience.

  734 137 MCP
• 50
  

  dbt MCP Server

  Bridge dbt projects and AI agents with rich project context.

  dbt MCP Server provides an implementation of the Model Context Protocol for dbt projects, enabling seamless integration between dbt and AI agents. It allows agents to access and understand the context of dbt Core, dbt Fusion, and dbt Platform projects. The tool supports connection to external AI products and offers resources for building custom agents. Documentation and examples are provided to facilitate adoption and integration.

  420 90 MCP