imagen3-mcp alternatives

1

@nanana-ai/mcp-server-nano-banana

MCP server for Nanana AI image generation using Gemini's nano banana model.

@nanana-ai/mcp-server-nano-banana serves as an MCP (Model Context Protocol) compatible server for facilitating image generation and transformation powered by the Gemini nano banana model. It enables clients like Claude Desktop to interact with Nanana AI, processing text prompts to generate images or transform existing images. The server can be easily configured with API tokens and integrated into desktop applications. Users can manage credentials, customize endpoints, and monitor credit usage seamlessly.

3 2 MCP

2

openai-gpt-image-mcp

MCP-compatible server for image generation and editing via OpenAI APIs.

Provides a Model Context Protocol (MCP) tool server that interfaces with OpenAI's GPT-4o/gpt-image-1 APIs to generate and edit images from text prompts. Supports advanced image editing operations including inpainting, outpainting, and compositing with customizable options. Integrates with MCP-compatible clients such as Claude Desktop, VSCode, Cursor, and Windsurf. Offers both base64 and file output for generated images, with automatic file handling for large images.

70 21 MCP

3

Outsource MCP

Unified MCP server for multi-provider AI text and image generation

Outsource MCP is a Model Context Protocol server that bridges AI applications with multiple model providers via a single unified interface. It enables AI tools and clients to access over 20 major providers for both text and image generation, streamlining model selection and API integration. Built on FastMCP and Agno agent frameworks, it supports flexible configuration and is compatible with MCP-enabled AI tools. Authentication is provider-specific, and all interactions use a simple standardized API format.

26 5 MCP

4

OpenAPI-MCP

Dockerized MCP server that transforms OpenAPI/Swagger specs into MCP-compatible tools.

OpenAPI-MCP is a dockerized server that reads Swagger/OpenAPI specification files and generates corresponding Model Context Protocol (MCP) toolsets. It enables MCP-compatible clients to interact dynamically with APIs described by OpenAPI specs, automatically generating the necessary tool schemas and facilitating secure API key handling. The solution supports both local and remote API specs, offers filtering by tags and operations, and can be easily deployed using Docker.

150 31 MCP

5

Replicate Flux MCP

MCP-compatible server for high-quality image and SVG generation via Replicate models.

Replicate Flux MCP is an advanced Model Context Protocol (MCP) server designed to enable AI assistants to generate high-quality raster images and vector graphics. It leverages Replicate's Flux Schnell model for image synthesis and Recraft V3 SVG model for vector output, supporting seamless integration with AI platforms like Cursor, Claude Desktop, Smithery, and Glama.ai. Users can generate images and SVGs by simply providing natural language prompts, with support for parameter customization, batch processing, and variant creation.

66 14 MCP

6

Amazon Bedrock MCP Server

Model Control Protocol server for AI image generation via Amazon Bedrock's Nova Canvas.

Amazon Bedrock MCP Server implements the Model Control Protocol to enable advanced AI image generation using Amazon's Nova Canvas model. It provides features like deterministic output through seed control, negative prompts, and configurable quality and image dimensions. Secure and flexible AWS credential management is supported, along with integration for Claude Desktop and robust input validation. The solution ensures high-quality, reproducible image generation workflows tailored for both developers and integrated applications.

22 12 MCP

7

Fal.ai MCP Server

MCP server for multimodal media generation using Fal.ai models.

Fal.ai MCP Server is a Model Context Protocol (MCP) compliant server that enables clients like Claude Desktop and others to generate images, videos, music, audio, and transcriptions using Fal.ai models. It offers native asynchronous operation and supports both STDIO and HTTP/SSE transports for flexible integration. The server provides high-performance media generation, including upscaling, text-to-speech, audio transcription, and image-to-image transformations, all powered by Fal.ai's API. Easy deployment options are available via Docker, PyPI, or from source.

9 4 MCP

8

McGravity

Unified load balancer and proxy for multiple MCP servers

McGravity acts as a scalable unified proxy and load balancer for multiple MCP (Model Context Protocol) servers. It allows clients to connect through a single endpoint to access and manage multiple MCP servers efficiently. The tool offers load balancing, configuration via YAML, CLI and Docker support, and plans to evolve with features such as health checks and a web interface. Designed for modern GenAI infrastructure, it simplifies connection, balancing, and scalability of MCP server deployments.

68 3 MCP

9

mcp-k8s

A Kubernetes MCP server enabling resource management via Model Control Protocol.

mcp-k8s is a Kubernetes server that implements the Model Control Protocol (MCP), allowing users to interact with Kubernetes clusters through MCP-compatible tools. It supports querying and managing all Kubernetes resources, including custom resources, with fine-grained control over read and write operations. The server utilizes stdio communication and integrates with both Kubernetes and Helm, facilitating resource and Helm release management. It is designed to support natural language interactions with large language models for managing, diagnosing, and learning Kubernetes operations.

129 25 MCP

10

books-mcp-server

A server implementation supporting Model Context Protocol integration with cherry-studio.

books-mcp-server allows users to set up a Model Context Protocol (MCP) compliant server for managing and interacting with AI models. It enables integration with cherry-studio through STDIO commands and structured server configurations. The tool provides straightforward setup instructions and supports launching the server with customizable parameters, making it suitable for various AI context management tasks.

5 2 MCP

11

Qiniu MCP Server

Bridge AI models to Qiniu cloud storage and multimedia services via the Model Context Protocol.

Qiniu MCP Server implements the Model Context Protocol (MCP) to enable AI model clients to seamlessly access Qiniu cloud storage, multimedia, and CDN services within the context of user interactions. It provides capabilities such as bucket and file listing, file uploading, file reading, image processing tasks like resizing and rounded corners, as well as CDN cache operations. The server is designed to be integrated with AI tooling like VS Code's Cline plugin, supporting contextual data access and manipulation via a standardized protocol.

30 13 MCP

12

mcp-server-templates

Deploy Model Context Protocol servers instantly with zero configuration.

MCP Server Templates enables rapid, zero-configuration deployment of production-ready Model Context Protocol (MCP) servers using Docker containers and a comprehensive CLI tool. It provides a library of ready-made templates for common integrations—including filesystems, GitHub, GitLab, and Zendesk—and features intelligent caching, smart tool discovery, and flexible configuration options via JSON, YAML, environment variables, or CLI. Perfect for AI developers, data scientists, and DevOps teams, it streamlines the process of setting up and managing MCP servers and has evolved into the MCP Platform for enhanced capabilities.

5 1 MCP

13

OCI Registry MCP Server

Expose OCI registry data to LLM-powered applications via the Model Context Protocol.

Implements a Model Context Protocol (MCP) server that enables language model applications to query OCI registries. Provides tools for retrieving image information, listing repository tags, and accessing manifests and configs. Features secure authentication support and seamless integration with ToolHive for containerized deployment. Empowers AI-driven systems to interact programmatically with container registries.

11 3 MCP

14

Portainer MCP

Connect AI assistants securely to Portainer environments using the Model Context Protocol.

Portainer MCP is an implementation of the Model Context Protocol (MCP) designed for seamless integration between AI assistants and Portainer-managed container environments. It enables management of Portainer resources and allows execution of Docker and Kubernetes commands through AI interfaces in a secure, standardized manner. The tool provides direct protocol-based access to environment data, facilitating automation and operational insights for container infrastructures.

81 16 MCP

15

mcp-access-point

Bridge HTTP services with Model Context Protocol (MCP) clients seamlessly.

MCP Access Point acts as a lightweight gateway that enables direct communication between MCP-compatible clients and traditional HTTP services without requiring server-side modifications. Built on the high-performance Pingora proxy library, it supports protocol conversion between HTTP, SSE, and MCP, supporting multi-tenancy and customizable routing. It empowers various MCP clients, such as Cursor Desktop, MCP Inspector, and VS Code, to interact with existing APIs efficiently. Configuration is flexible via YAML, and deployment is possible both locally and through Docker.

118 21 MCP

16

MCP ECharts

Dynamically generate Apache ECharts visualizations via Model Context Protocol (MCP).

MCP ECharts enables dynamic generation of Apache ECharts visualizations through the Model Context Protocol, supporting interactions with AI models. It provides multiple transport options (stdio, SSE, streamable) and integrates with platforms like Claude, VSCode, and Smithery. The tool allows exporting charts in PNG, SVG, and option formats, with optional MinIO storage for enhanced sharing and performance. Featuring zero dependencies and local secure rendering, it is easily deployable and versatile for a range of visualization workflows.

153 29 MCP

17

MCP Server Kubernetes

Connect and manage Kubernetes clusters via Model Context Protocol servers.

MCP Server Kubernetes enables seamless connection and management of Kubernetes clusters through the Model Context Protocol. It supports loading kubeconfig from multiple sources, integrates easily with Claude Code, Claude Desktop, and VS Code, and offers flexible authentication mechanisms. Users can control clusters using standard command-line tools and extension integrations for multiple environments.

1,181 194 MCP

18

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

19

k8s-mcp-server

Securely enable Claude to run Kubernetes CLI tools via Anthropic's Model Context Protocol.

K8s MCP Server provides a Docker-based implementation of Anthropic's Model Context Protocol (MCP), allowing Claude to securely execute Kubernetes CLI tools such as kubectl, helm, istioctl, and argocd within a containerized environment. It integrates with Claude Desktop so users can interact with their Kubernetes clusters using natural language. The server emphasizes security by operating as a non-root user and offering strict command validation, while also supporting major cloud providers like AWS, Google Cloud, and Azure. Easy configuration and support for various Unix tools further enhance its capabilities.

166 31 MCP

20

manim-mcp-server

MCP server for generating Manim animations on demand.

Manim MCP Server allows users to execute Manim Python scripts via a standardized protocol, generating animation videos that are returned as output. It integrates with systems like Claude to dynamically render animation content from user scripts and supports configurable deployment using environment variables. The server handles management of output files and cleanup of temporary resources, designed with portability and ease of integration in mind.

454 48 MCP

21

OpenMCP

A standard and registry for converting web APIs into MCP servers.

OpenMCP defines a standard for converting various web APIs into servers compatible with the Model Context Protocol (MCP), enabling efficient, token-aware communication with client LLMs. It also provides an open-source registry of compliant servers, allowing clients to access a wide array of external services. The platform supports integration with local and remote hosting environments and offers tools for configuring supported clients, such as Claude desktop and Cursor. Comprehensive guidance is offered for adapting different API formats including REST, gRPC, GraphQL, and more into MCP endpoints.

252 27 MCP

22

FHIR MCP Server

A Model Context Protocol server for seamless interaction with FHIR resources and AI tools.

FHIR MCP Server implements a full Model Context Protocol server, enabling large language model agents to perform comprehensive CRUD operations on FHIR-compliant healthcare data. It offers standardized integration with various clinical data sources, natural-language query capabilities, and supports secure authentication via OAuth2. The server includes semantic search, AI-powered document processing, terminology resolution, Docker deployment, and is optimized for use with MCP-compatible clients like Claude Desktop.

34 5 MCP

23

mcpmcp-server

Seamlessly discover, set up, and integrate MCP servers with AI clients.

mcpmcp-server enables users to discover, configure, and connect MCP servers with preferred clients, optimizing AI integration into daily workflows. It supports streamlined setup via JSON configuration, ensuring compatibility with various platforms such as Claude Desktop on macOS. The project simplifies the connection process between AI clients and remote Model Context Protocol servers. Users are directed to an associated homepage for further platform-specific guidance.

17 6 MCP

24

mcp-image-compression

High-performance image compression microservice based on MCP architecture.

mcp-image-compression is a microservice designed for fast and efficient compression of images, supporting multiple mainstream formats such as JPEG, PNG, WebP, and AVIF. Built with the Model Context Protocol (MCP) architecture, it enables developers to optimize image resources for better web and app performance. The service features smart compression, batch processing, and customizable quality control, suitable for both offline and online workflows.

28 6 MCP

25

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

26

K8M

AI-driven lightweight Kubernetes dashboard with integrated MCP and multi-cluster management.

K8M is an AI-enabled mini Kubernetes dashboard built with a focus on simplifying cluster management and enhancing user experience. Utilizing the Model Context Protocol (MCP), K8M offers visual management for MCP, allowing AI models to interact with Kubernetes resources and tools easily, supporting over 49 built-in MCP tools. It enables powerful multi-cluster management, integrates advanced AI capabilities such as chat-driven resource explanation and diagnostics, and supports custom large model integration including private deployments and models like Ollama.

702 119 MCP

27

MKP

A Model Context Protocol server enabling LLM-powered applications to interact with Kubernetes clusters.

MKP is a Model Context Protocol (MCP) server designed for Kubernetes environments, allowing large language model (LLM) powered applications to list, retrieve, and apply Kubernetes resources through a standardized protocol interface. Built natively in Go, it utilizes Kubernetes API machinery to provide direct, type-safe, and reliable operations without dependencies on CLI tools. MKP offers a minimalist, pluggable design enabling universal resource support, including custom resource definitions, and includes built-in rate limiting for production readiness.

54 5 MCP

28

magg

Meta-MCP aggregator and manager for LLM capability extension.

Magg is a server that implements the Model Context Protocol (MCP), acting as a central aggregator and proxy for multiple MCP servers. It enables Large Language Models (LLMs) to dynamically discover, add, configure, and manage external tools at runtime. By aggregating tools from different MCP servers under unified namespaces, it streamlines capability management and introduces features such as configuration persistence, authentication, and real-time notifications. Magg offers both command-line and Docker deployment, with support for HTTP, stdio, and in-memory transport.

62 14 MCP

29

cloudflare/mcp-server-cloudflare

Connect Cloudflare services to Model Context Protocol (MCP) clients for AI-powered management.

Cloudflare MCP Server enables integration between Cloudflare's suite of services and clients using the Model Context Protocol (MCP). It provides multiple specialized servers that allow AI models to access, analyze, and manage configurations, logs, analytics, and other features across Cloudflare's platform. Users can leverage natural language interfaces in compatible MCP clients to read data, gain insights, and perform automated actions on their Cloudflare accounts. This project aims to streamline the orchestration of security, development, monitoring, and infrastructure tasks through standardized MCP connections.

2,919 251 MCP

30

pluggedin-mcp-proxy

Unified proxy server for Model Context Protocol data exchanges and AI integrations

Aggregates multiple Model Context Protocol (MCP) servers into a single, unified proxy interface, supporting real-time discovery, management, and orchestration of AI model resources, tools, and prompts. Enables seamless interaction between MCP clients such as Claude, Cline, and Cursor, while integrating advanced document search, AI document exchange, and workspace management. Provides flexible transport modes (STDIO and Streamable HTTP), robust authentication, and comprehensive security measures for safe and scalable AI data exchange.

87 15 MCP

31

mcp

Universal remote MCP server connecting AI clients to productivity tools.

WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.

27 6 MCP

32

tfmcp

A CLI tool for managing Terraform via the Model Context Protocol (MCP).

tfmcp is a command-line tool that enables interaction with Terraform using the Model Context Protocol (MCP). It allows language models and AI assistants to analyze, manage, and operate Terraform environments programmatically, supporting operations such as configuration analysis, state management, and secure application of changes. The tool offers enterprise-grade security, audit logging, and flexible deployment options including Docker support. Designed for efficiency and seamless integration, tfmcp simplifies infrastructure automation workflows for both developers and AI systems.

345 23 MCP

33

Kubernetes MCP Server

A standardized MCP interface for Kubernetes cluster management and introspection.

Kubernetes MCP Server enables interaction with Kubernetes clusters via the Model Context Protocol, providing a consistent and standardized interface across various tools and environments. It features resource discovery, detailed inspection, metrics retrieval, resource manipulation, and supports multiple communication modes such as stdio, SSE, and streamable HTTP. Designed for flexibility and security, it allows both read-only and full-access modes and works with different Kubernetes contexts.

117 21 MCP

34

quran-mcp-server

MCP server to access Quran.com API with AI tool compatibility.

quran-mcp-server exposes the Quran.com corpus and associated data through a Model Context Protocol (MCP) server generated from an OpenAPI specification. It provides tool endpoints for chapters, verses, translations, tafsirs, audio, languages, and more. The server is designed for seamless integration with large language models (LLMs) and AI tools, supporting both Docker and Node.js environments. Advanced logging features and flexible deployment options are included for debugging and development.

49 10 MCP

35

container-use

Containerized environments for coding agents.

container-use enables coding agents to operate in parallel, isolated container environments integrated with the Model Context Protocol (MCP). Agents work independently in designated git branches, ensuring safe experimentation and real-time monitoring. The tool supports direct terminal access, seamless workflow integration, and works with any MCP-compatible agent, including Claude Code and Cursor. Designed for flexibility and visibility, it is suitable for managing multiple coding agents concurrently.

3,248 169 MCP

36

mcp-open-library

Model Context Protocol server for accessing Open Library book and author data.

Provides an implementation of a Model Context Protocol (MCP) server to enable AI assistants and clients to search and retrieve book and author information from the Open Library API. Supports searching by title, author name, and various identifiers, as well as fetching author photos and book covers. Returns structured, machine-readable data suitable for AI model context integration. Offers installation via Smithery, manual setup, and Docker deployment.

34 9 MCP

37

Tilt MCP Server

Programmatic Access to Tilt via Model Context Protocol for LLMs

Tilt MCP Server provides Model Context Protocol (MCP) capabilities to enable seamless integration between Tilt—an environment for managing Docker/Kubernetes workloads—and large language model (LLM) applications. It allows LLMs and AI assistants to interact programmatically with Tilt resources, retrieve logs, monitor status, trigger actions, and utilize guided workflows. The server exposes standardized resources, tools, and prompts for intelligent management and automation of Tilt-based development environments.

2 1 MCP

38

PythonAnywhere Model Context Protocol Server

Bridge AI-powered tools with PythonAnywhere for secure, programmatic environment management.

PythonAnywhere Model Context Protocol Server implements the MCP, allowing AI clients and automation tools to securely manage files, web apps, and scheduled tasks within a PythonAnywhere account. It offers a standardized interface to perform core operations like editing files, deploying or managing web apps, and handling scheduled jobs with fine-grained access control. Designed for integration with tools such as Claude Desktop, GitHub Copilot, and Cursor, it ensures auditability of actions and supports multiple installation workflows.

8 4 MCP

39

mcp-server

A production-ready Model Context Protocol server for advanced aerospace and astrodynamics calculations.

The mcp-server provides a Model Context Protocol (MCP) server specifically designed for aerospace and astrodynamics computations. It offers both STDIO and HTTP/SSE transport options, enabling seamless integration with MCP clients for tasks like celestial body ephemeris, orbital mechanics, geometry, ground station operations, and time system conversions. Powered by the IO Aerospace Astrodynamics framework, it supports rapid, context-aware scientific tool execution for applications in mission analysis and research. Extensible deployment methods, including Docker and .NET, and a focus on easy client integration are core components.

1 1 MCP

40

blender-mcp

Seamless integration between Blender and Claude AI using the Model Context Protocol.

BlenderMCP enables direct interaction between Blender and Claude AI by leveraging the Model Context Protocol (MCP). It allows users to create, manipulate, and inspect 3D scenes in Blender through natural language commands sent to Claude, which communicates with Blender via a custom socket server and an addon. The solution features two-way communication, object and material manipulation, code execution within Blender, and easy integration with tools like Cursor, Visual Studio Code, and Claude for Desktop.

13,092 1,232 MCP

41

awslabs/mcp

Specialized MCP servers for seamless AWS integration in AI and development environments.

AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.

6,220 829 MCP

42

anyquery

Universal SQL query engine for files, databases, apps, and LLM integration.

Anyquery is a SQL query engine that enables users to run SQL queries on a wide array of data sources, including files, databases, and popular applications via plugins. It supports integrations with large language models (LLMs) through the Model Context Protocol (MCP), providing seamless access for AI models to query data. Built on SQLite, it extends functionality with a plugin system and can also function as a MySQL server for compatibility with conventional SQL clients. Its flexible installation options and broad plugin ecosystem allow extensive customization and integration.

1,298 77 MCP

43

video-editing-mcp

MCP server for uploading, editing, searching, and generating videos via Video Jungle and LLMs.

Implements a Model Context Protocol (MCP) server for seamless video uploading, editing, searching, and generative editing workflows, powered by Video Jungle integration and LLM assistance. Provides a suite of tools for video asset management, automated video editing, and context-aware search leveraging multimedia analysis. Supports both cloud workflows through Video Jungle and local searching capabilities, such as accessing the Photos app database on MacOS. Designed for integration with clients like Claude Desktop and supports automation, debugging, and development through open protocols.

207 27 MCP

44

Redis Cloud API MCP Server

Natural language interface for managing Redis Cloud via Model Context Protocol

Provides a Model Context Protocol (MCP) server that enables users to manage Redis Cloud resources and accounts using natural language commands. Supports integration with clients such as Claude Desktop and Cursor IDE, facilitating operations such as creating databases, managing subscriptions, retrieving billing information, and monitoring tasks. Offers standardized endpoints to simplify cloud provider and plan selection, as well as database module configuration and task tracking.

37 16 MCP

45

mindsdb

Connect, unify, and query data at scale with an open-source AI platform.

MindsDB enables seamless connection to and unification of data from hundreds of enterprise sources, allowing for highly accurate responses across large-scale federated systems. It provides an open-source server with built-in support for the Model Context Protocol (MCP) to facilitate standardized interaction with AI-driven question answering over diverse data sets. The platform offers tools for preparing, organizing, and transforming both structured and unstructured data via knowledge bases, views, and scheduled jobs. Its agent framework and SQL interface empower users to configure data-centric agents, automate workflows, and interact with data conversationally.

35,487 5,735 MCP

46

mcp-server-js

Enable secure, AI-driven process automation and code execution on YepCode via Model Context Protocol.

YepCode MCP Server acts as a Model Context Protocol (MCP) server that facilitates seamless communication between AI platforms and YepCode’s workflow automation infrastructure. It allows AI assistants and clients to execute code, manage environment variables, and interact with storage through standardized tools. The server can expose YepCode processes directly as MCP tools and supports both hosted and local installations via NPX or Docker. Enterprise-grade security and real-time interaction make it suitable for integrating advanced automation into AI-powered environments.

31 13 MCP

47

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

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