mcp-stockfish alternatives

1

MCP Tic-Tac-Toe

A Model Context Protocol server for playing and analyzing tic-tac-toe games through standardized tool interfaces.

MCP Tic-Tac-Toe is a server implementation that provides a complete set of MCP tools for playing, managing, and analyzing tic-tac-toe games. It supports interactions with AI assistants such as Claude, enabling features like creating multiple parallel sessions, making moves, providing strategic analysis, and managing game context. The server is designed for easy integration with clients through various transport methods, including stdio and SSE, and supports seamless AI-human collaboration.

2 1 MCP

2

ws-mcp

WebSocket bridge for MCP stdio servers.

ws-mcp wraps Model Context Protocol (MCP) stdio servers with a WebSocket interface, enabling seamless integration with web-based clients and tools. It allows users to configure and launch multiple MCP servers via a flexible configuration file or command-line arguments. The tool is designed to be compatible with services such as wcgw, fetch, and other MCP-compliant servers, providing standardized access to system operations, HTTP requests, and more. Integration with tools like Kibitz enables broader applications in model interaction workflows.

19 7 MCP

3

MCP Zotero

Model Context Protocol server for seamless Zotero integration with AI tools.

MCP Zotero provides a Model Context Protocol server enabling AI models such as Claude to access and interact with Zotero libraries. Users can securely link their Zotero accounts and perform actions including listing collections, retrieving papers, searching the library, and getting details about specific items. Integration is designed for both standalone operation and as an extension for tools like Claude Desktop.

137 17 MCP

4

mcp-server-chatsum

Summarize and query chat messages using the MCP Server protocol.

mcp-server-chatsum is an MCP Server designed to summarize and query chat messages. It provides tools to interact with chat data, enabling users to extract and summarize message content based on specified prompts. The server can be integrated with Claude Desktop and supports communication over stdio, offering dedicated debugging tools via the MCP Inspector. Environment variable support and database integration ensure flexible deployment for chat data management.

1,024 99 MCP

5

Graphlit MCP Server

Integrate and unify knowledge sources for RAG-ready AI context with the Graphlit MCP Server.

Graphlit MCP Server provides a Model Context Protocol interface, enabling seamless integration between MCP clients and the Graphlit platform. It supports ingestion from a wide array of sources such as Slack, Discord, Google Drive, email, Jira, and GitHub, turning them into a searchable, RAG-ready knowledge base. Built-in tools allow for document, media extraction, web crawling, and web search, as well as advanced retrieval and publishing functionalities. The server facilitates easy configuration, sophisticated data operations, and automated notifications for diverse workflows.

369 49 MCP

6

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

7

Cloudbet Sports MCP Server

Minimal MCP server for sports data and betting tool exposure via Cloudbet API.

Implements a minimal, single-file server adhering to the Model Context Protocol (MCP) for exposing sports data and betting tools using the Cloudbet public API. Designed for educational and demonstration purposes, it follows the MCP Server specification and enables users to list and call tools via JSON-RPC. Provides examples for listing available tools and invoking actions such as retrieving sports events and markets. Intended for quick experiments and integration scenarios.

9 3 MCP

8

MCP Ping-Pong Server by Remote Call

An experimental MCP-based Ping-Pong server leveraging FastAPI and FastMCP for remote calls.

MCP Ping-Pong Server by Remote Call demonstrates the use of the Model Context Protocol (MCP) for handling command-based interactions via FastAPI. The project provides a backend powered by FastAPI and FastMCP, enabling remote MCP calls through API endpoints and Server-Sent Events (SSE). It includes thread-safe session management, command handling integration, and an interactive UI for engaging with ping, pong, and count operations. Designed as an educational tool, it showcases practical MCP usage for API-driven workflows.

1 2 MCP

9

MCP Chess Server

Play chess against any LLM via Model Context Protocol tools.

MCP Chess Server enables interactive chess gameplay between users and any large language model (LLM) by exposing standardized model context protocol tools. Users can play chess, analyze games from PGN files, and visualize board states through a variety of programmatically accessible functions. The system supports move validation, game state visualization, turn detection, and position finding within PGN strings, making it suitable for both human and automated (AI/LLM-driven) play and analysis.

14 6 MCP

10

Chess.com MCP Server

Standardized MCP server for accessing and analyzing Chess.com public data

Provides a Model Context Protocol (MCP) server that interfaces with Chess.com's public API, enabling AI assistants and applications to access player data, game records, clubs, and titled players through standardized tools. Offers Docker and UV-based deployment, and is configurable to suit specific assistant and client requirements. Supports seamless integration with Claude Desktop and exposes multiple ready-to-use tools for chess data retrieval and analysis.

54 15 MCP

11

mcp-shell

A secure Model Context Protocol (MCP) server for AI-driven shell command execution.

mcp-shell enables AI assistants and MCP clients to securely execute shell commands via the standardized Model Context Protocol. Built in Go and leveraging the official MCP SDK, it facilitates structured, auditable, and context-aware access to shell environments. The server emphasizes security through Docker isolation, command validation, resource limits, and comprehensive audit logging.

44 8 MCP

12

buildkite-mcp-server

Server exposing Buildkite data through the Model Context Protocol for AI integration.

buildkite-mcp-server implements a Model Context Protocol (MCP) server that exposes Buildkite data, including pipelines, builds, jobs, and tests, to AI tooling and editors. It facilitates secure and standardized access to CI/CD information for model-based tools. The project is written in Go and is recommended to be run in a containerized, secure environment.

40 21 MCP

13

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

14

QuantConnect MCP Server

Official bridge for secure AI access to QuantConnect's algorithmic trading cloud platform

QuantConnect MCP Server enables artificial intelligence systems such as Claude and OpenAI to interface with QuantConnect's cloud platform through an official, secure, and dockerized implementation of the Model Context Protocol (MCP). It facilitates automated project management, strategy writing, backtesting, and live deployment by exposing a comprehensive suite of API tools for users with valid access credentials. As the maintained official version, it ensures security, easy deployment, and cross-platform compatibility for advanced algorithmic trading automation.

50 19 MCP

15

mcp-trino

A fast Go-based MCP server for seamless Trino SQL access.

mcp-trino is a Model Context Protocol (MCP) server implemented in Go, designed for high-performance integration with Trino's distributed SQL engine. It enables AI assistants and clients to issue SQL queries, discover catalogs, schemas, and tables, and fetch schema information through standardized MCP tools over HTTP and STDIO transports. The solution supports optional OAuth2 authentication, connects to a variety of data sources through Trino, and is available as a Docker container.

79 29 MCP

16

MCP Shell Server

A secure, configurable shell command execution server implementing the Model Context Protocol.

MCP Shell Server provides secure remote execution of whitelisted shell commands via the Model Context Protocol (MCP). It supports standard input, command output retrieval, and enforces strict safety checks on command operations. The tool allows configuration of allowed commands and execution timeouts, and can be integrated with platforms such as Claude.app and Smithery. With robust security assessments and flexible deployment methods, it facilitates controlled shell access for AI agents.

153 42 MCP

17

MCP Proxy Monorepo

Monorepo for MCP (Model Control Protocol) servers enabling AI integrations.

MCP Proxy Monorepo provides servers implementing the Model Control Protocol (MCP) for integrating AI services, particularly through Bitte AI. It offers a structured framework for hosting and developing MCP-compliant server packages and supports scalable, multi-service deployments. The project is built using Bun for the JavaScript runtime, Turborepo for monorepo management, and includes tools for development, code quality, and package extensibility.

13 2 MCP

18

mcp-server-docker

Natural language management of Docker containers via Model Context Protocol.

mcp-server-docker enables users to manage Docker containers using natural language instructions through the Model Context Protocol. It allows composing, introspecting, and debugging containers, as well as managing persistent Docker volumes. The tool is suitable for server administrators, tinkerers, and AI enthusiasts looking to leverage LLM capabilities for Docker management. Integration with tools like Claude Desktop and Docker ensures flexible deployment and easy connectivity to Docker engines.

648 86 MCP

19

Godot MCP

A Model Context Protocol (MCP) server implementation using Godot and Node.js.

Godot MCP implements the Model Context Protocol (MCP) as a server, leveraging the Godot game engine along with Node.js and TypeScript technologies. Designed for seamless integration and efficient context management, it aims to facilitate standardized communication between AI models and applications. This project offers a ready-to-use MCP server for developers utilizing Godot and modern JavaScript stacks.

1,071 124 MCP

20

Kafka Schema Registry MCP Server

MCP-compliant server for advanced Kafka Schema Registry management and integration.

Kafka Schema Registry MCP Server is a fully-compliant Model Context Protocol (MCP) server built with the FastMCP 2.8.0+ framework. It provides advanced schema context support, enables multi-registry management, and offers comprehensive schema export capabilities. The tool is designed for seamless integration with Claude Desktop and other MCP clients using JSON-RPC over stdio. It supports Docker-based deployment and includes features to streamline both administrator and end-user workflows.

26 7 MCP

21

Sequa MCP

Bridge Sequa's advanced context engine to any MCP-capable AI client.

Sequa MCP acts as a seamless integration layer, connecting Sequa’s knowledge engine with various AI coding assistants and IDEs via the Model Context Protocol (MCP). It enables tools to leverage Sequa’s contextual knowledge streams, enhancing code understanding and task execution across multiple repositories. The solution provides a simple proxy command to interface with standardized MCP transports, supporting configuration in popular environments such as Cursor, Claude, VSCode, and others. Its core purpose is to deliver deep, project-specific context to LLM agents through a unified and streamable endpoint.

16 3 MCP

22

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

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

Octocode MCP

Enterprise-grade AI context server for codebase research and analysis.

Octocode MCP is a Model Context Protocol (MCP) server designed to enable AI assistants to search, analyze, and extract insights from millions of GitHub repositories with high security and token efficiency. It offers intelligent orchestration for deep code research, planning, and agentic workflows, streamlining the process of building and understanding complex software projects. The platform features robust tools and commands, such as /research for expert code research, designed to support developers and AI systems with context-rich information.

577 45 MCP

25

Codex MCP Server

An MCP-compatible server delivering enriched blockchain data for AI models.

Codex MCP Server implements the Model Context Protocol to provide enriched blockchain data from Codex. It is compatible with MCP clients such as Claude Desktop and Claude CLI, allowing seamless integration in AI workflows that require blockchain context. Users can run the server locally or via npx, and configure it for various MCP-compatible tools using their Codex API key.

20 4 MCP

26

CCXT MCP Server

Unified Model Context Protocol gateway for cryptocurrency exchange integration

CCXT MCP Server provides a high-performance gateway integrating multiple cryptocurrency exchanges with language models via the Model Context Protocol (MCP). It connects LLMs, such as Claude and GPT, to real-time market data and trading operations through a standardized interface. Leveraging the CCXT library, it supports various exchanges, different market types, advanced caching, and proxy configuration options. The server is optimized for maintainability with modular architecture, enabling seamless interaction and extensibility.

117 23 MCP

27

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

28

Insforge MCP Server

A Model Context Protocol server for seamless integration with Insforge and compatible AI clients.

Insforge MCP Server implements the Model Context Protocol (MCP), enabling smooth integration with various AI tools and clients. It allows users to configure and manage connections to the Insforge platform, providing automated and manual installation methods. The server supports multiple AI clients such as Claude Code, Cursor, Windsurf, Cline, Roo Code, and Trae via standardized context management. Documentation and configuration guidelines are available for further customization and usage.

3 2 MCP

29

WebSearch-MCP

Real-time web search for AI assistants via Model Context Protocol.

WebSearch-MCP is a Model Context Protocol (MCP) server that enables real-time web search capabilities for AI assistants through the stdio transport. It connects with a web crawler API to retrieve up-to-date search results and serves these results to AI models like Claude. The solution offers straightforward configuration and seamless integration with various MCP clients, enhancing AI model access to current and relevant external information.

19 7 MCP

30

mcp-confluent

MCP server for managing Confluent Cloud resources via natural language.

mcp-confluent is a Model Context Protocol (MCP) server implementation designed to enable natural language interaction with Confluent Cloud REST APIs. It integrates with AI tools such as Claude Desktop and Goose CLI, allowing users to manage Kafka topics, connectors, and Flink SQL statements conversationally. The project offers flexible configuration, CLI usage, and supports various transports for secure and customizable operations.

115 36 MCP

31

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

32

mcp-memgraph

Expose Memgraph database features via the Model Context Protocol.

mcp-memgraph provides an MCP (Model Context Protocol) server implementation, enabling Memgraph tools to be accessed over a lightweight STDIO protocol. It supports seamless integration with AI frameworks by standardizing context and communication for data-driven AI workflows. The toolkit is part of a larger suite for extending Memgraph with AI-powered capabilities, including tools for LangChain integration and automated database migration. Tested packages and usage examples are provided for quick adoption.

52 5 MCP

33

CMD MCP Server

Execute CMD commands via the Model Context Protocol with cross-platform and SSH support.

CMD MCP Server is an implementation of the Model Context Protocol (MCP) for executing CMD commands on Windows and Linux systems, with additional support for SSH connections. It enables seamless integration of command-line operations with MCP-compatible applications, leveraging the official MCP SDK. Written in TypeScript for cross-platform compatibility, it allows programmatic execution, configuration, and extension of CMD operations through standardized protocols. The server is designed for easy installation, robust configuration, and developer-friendly extension.

22 11 MCP

34

docker-mcp

A powerful MCP server for seamless Docker container and compose stack management.

docker-mcp is a Model Context Protocol (MCP) server that enables robust Docker container and compose stack management via Claude AI. It offers easy installation through Smithery or manual setup, supporting container creation, Docker Compose stack deployment, log retrieval, and monitoring. Integration with the Claude Desktop app is straightforward, and the included MCP Inspector aids debugging. This tool simplifies Docker operations for automation and AI model interactions.

419 57 MCP

35

Pica MCP Server

A Model Context Protocol (MCP) server for seamless integration with 100+ platforms via Pica.

Pica MCP Server provides a standardized Model Context Protocol (MCP) interface for interaction with a wide range of third-party services through Pica. It enables direct platform integrations, action execution, and intelligent intent detection while prioritizing secure environment variable management. The server also offers features such as code generation, form and data handling, and robust documentation for platform actions. It supports multiple deployment methods, including standalone, Docker, Vercel, and integration with tools like Claude Desktop and Cursor.

8 5 MCP

36

MCP Server for Iaptic

A Model Context Protocol server for accessing and managing Iaptic data with AI agents.

MCP Server for Iaptic implements the Model Context Protocol to enable AI models, such as Claude, to securely and efficiently interact with Iaptic's customer, purchase, transaction, and statistics data. The server provides a standardized interface and command set for querying and managing information related to customers, purchases, transactions, events, and application management. Designed for integration with Claude Desktop and similar AI clients, it offers both automated and manual installation options.

5 7 MCP

37

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

38

Flowcore Platform MCP Server

A standardized MCP server for managing and interacting with Flowcore Platform resources.

Flowcore Platform MCP Server provides an implementation of the Model Context Protocol (MCP) for seamless interaction and management of Flowcore resources. It enables AI assistants to query and control the Flowcore Platform using a structured API, allowing for enhanced context handling and data access. The server supports easy deployment with npx, npm, or Bun and requires user authentication using Flowcore credentials.

9 5 MCP

39

Firefly MCP Server

Seamless resource discovery and codification for Cloud and SaaS with Model Context Protocol integration.

Firefly MCP Server is a TypeScript-based server implementing the Model Context Protocol to enable integration with the Firefly platform for discovering and managing resources across Cloud and SaaS accounts. It supports secure authentication, resource codification into infrastructure as code, and easy integration with tools such as Claude and Cursor. The server can be configured via environment variables or command line and communicates using standardized MCP interfaces. Its features facilitate automation and codification workflows for cloud resource management.

15 6 MCP

40

CircleCI MCP Server

Enable LLM-driven automation for CircleCI with the Model Context Protocol.

CircleCI MCP Server is an implementation of the Model Context Protocol (MCP) designed to bridge CircleCI with large language models and AI assistants. It supports integration with tools like Cursor IDE, Windsurf, Copilot, and VS Code, allowing users to interact with CircleCI using natural language. The server can be deployed locally via NPX or Docker and remotely, making CircleCI workflows accessible and manageable through standardized protocol operations.

69 38 MCP

41

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

42

Dexscreener MCP server

MCP-compliant server for accessing the Dexscreener API.

Dexscreener MCP server provides a basic Model Context Protocol (MCP) interface to the Dexscreener API, allowing integration with tools like Claude Desktop. It supports both STDIO and server-sent events (SSE) modes and facilitates contextual API access based on the latest Dexscreener documentation. Configuration is straightforward for users on both MacOS and Windows, and the server can be tested using Inspector or other MCP-compatible clients.

16 4 MCP

43

Snowflake MCP Server

MCP server enabling secure and structured Snowflake database interaction with AI tools.

Snowflake MCP Server provides a Model Context Protocol-conformant interface to interact programmatically with Snowflake databases. It exposes SQL execution, schema exploration, and insight aggregation as standardized resources and tools accessible by AI assistants. The server offers read/write capabilities, structured resource summaries, and insight memoization suitable for contextual AI workflows. Integration is supported with popular AI platforms such as Claude Desktop via Smithery or UVX configurations.

170 75 MCP

44

MCP Server for Milvus

Bridge Milvus vector database with AI apps using Model Context Protocol (MCP).

MCP Server for Milvus enables seamless integration between the Milvus vector database and large language model (LLM) applications via the Model Context Protocol. It exposes Milvus functionality to external LLM-powered tools through both stdio and Server-Sent Events communication modes. The solution is compatible with MCP-enabled clients such as Claude Desktop and Cursor, supporting easy access to relevant vector data for enhanced AI workflows. Configuration is flexible through environment variables or command-line arguments.

196 57 MCP

45

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

46

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

47

Neovim MCP Server

Connect AI assistants to Neovim via the Model Context Protocol.

Neovim MCP Server enables seamless integration between Neovim instances and AI assistants by implementing the Model Context Protocol (MCP). It allows for multi-connection management, supports both stdio and HTTP server transport modes, and provides access to structured diagnostic information via URI schemes. With LSP integration, plugin support, and an extensible tool system, it facilitates advanced interaction with Neovim for context-aware AI workflows.

20 3 MCP

48

Opik MCP Server

A unified Model Context Protocol server for Opik with multi-transport IDE integration.

Opik MCP Server is an open-source implementation of the Model Context Protocol (MCP) designed for the Opik platform. It enables seamless integration with compatible IDEs and provides a unified interface to manage Opik's features such as prompts, projects, traces, and metrics. Supporting multiple transport mechanisms like stdio and experimental SSE, it simplifies workflow integration and platform management for LLM applications. The tool aims to streamline development and monitoring by offering standardized access and control over Opik's capabilities.

182 27 MCP

49

Flipt MCP Server

MCP server for Flipt, enabling AI assistants to manage and evaluate feature flags.

Flipt MCP Server is an implementation of the Model Context Protocol (MCP) that provides AI assistants with the ability to interact with Flipt feature flags. It enables listing, creating, updating, and deleting various flag-related entities, as well as flag evaluation and management. The server supports multiple transports, is configurable via environment variables, and can be deployed via npm or Docker. Designed for seamless integration with MCP-compatible AI clients.

2 7 MCP

50

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

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