Memory MCP alternatives

1

Agentic Long-Term Memory with Notion Integration

Production-ready agentic long-term memory and Notion integration with Model Context Protocol support.

Agentic Long-Term Memory with Notion Integration enables AI agents to incorporate advanced long-term memory capabilities using both vector and graph databases. It offers comprehensive Notion workspace integration along with a production-ready Model Context Protocol (MCP) server supporting HTTP and stdio transports. The tool facilitates context management, tool discovery, and advanced function chaining for complex agentic workflows.

4 2 MCP

2

MCP CLI

A powerful CLI for seamless interaction with Model Context Protocol servers and advanced LLMs.

MCP CLI is a modular command-line interface designed for interacting with Model Context Protocol (MCP) servers and managing conversations with large language models. It integrates with the CHUK Tool Processor and CHUK-LLM to provide real-time chat, interactive command shells, and automation capabilities. The system supports a wide array of AI providers and models, advanced tool usage, context management, and performance metrics. Rich output formatting, concurrent tool execution, and flexible configuration make it suitable for both end-users and developers.

1,755 299 MCP

3

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

4

Raindrop.io MCP Server

Enable LLMs to manage and search Raindrop.io bookmarks via the Model Context Protocol.

Raindrop.io MCP Server is an integration that allows large language models to interact with Raindrop.io bookmarks using the Model Context Protocol. It provides tools to create and search bookmarks, including filtering by tags, and is designed for interoperability with environments like Claude for Desktop. Installation can be done via Smithery or manually, and configuration is managed through environment variables. The project is open source and optimized for secure, tokenized access to Raindrop.io.

63 15 MCP

5

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

6

OpenStreetMap MCP Server

Enhancing LLMs with geospatial and location-based capabilities via the Model Context Protocol.

OpenStreetMap MCP Server enables large language models to interact with rich geospatial data and location-based services through a standardized protocol. It provides APIs and tools for address geocoding, reverse geocoding, points of interest search, route directions, and neighborhood analysis. The server exposes location-related resources and tools, making it compatible with MCP hosts for seamless LLM integration.

134 30 MCP

7

Model Context Protocol Servers (Archived)

Archived reference implementations of Model Context Protocol servers for various data sources.

Provides historical reference implementations of servers that demonstrate features and SDK capabilities of the Model Context Protocol (MCP). Covers integrations with a variety of services such as AWS KB Retrieval, Brave Search, GitHub, Google Drive, PostgreSQL, Redis, and more. These implementations are no longer maintained and are intended solely for archival and educational purposes.

180 108 MCP

8

FastMCP

TypeScript framework for building robust MCP servers with minimal setup.

FastMCP is a TypeScript framework designed for building servers that adhere to the Model Context Protocol (MCP), enabling efficient management of client sessions and context. It streamlines the creation of MCP servers by providing intuitive APIs, built-in authentication, session and request tracking, and support for handling various content types such as images and audio. The framework also enforces best practices around error handling, logging, and streaming outputs. Developers benefit from reduced boilerplate and a focus on core MCP functionality.

2,738 231 MCP

9

Stape MCP Server

An MCP server implementation for integrating Stape with AI model context protocols.

Stape MCP Server provides an implementation of the Model Context Protocol server tailored for the Stape platform. It enables secure and standardized access to model context capabilities, allowing integration with tools such as Claude Desktop and Cursor AI. Users can easily configure and authenticate MCP connections using provided configuration samples, while managing context and credentials securely. The server is open source and maintained by the Stape Team under the Apache 2.0 license.

4 3 MCP

10

Cross-LLM MCP Server

Unified MCP server for accessing and combining multiple LLM APIs.

Cross-LLM MCP Server is a Model Context Protocol (MCP) server enabling seamless access to a range of Large Language Model APIs including ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, and Mistral. It provides a unified interface for invoking different LLMs from any MCP-compatible client, allowing users to call and aggregate responses across providers. The server implements eight specialized tools for interacting with these LLMs, each offering configurable options like model selection, temperature, and token limits. Output includes model context details as well as token usage statistics for each response.

9 5 MCP

11

GIS MCP Server

Empower AI with advanced geospatial operations via Model Context Protocol.

GIS MCP Server provides a Model Context Protocol (MCP) server implementation that enables Large Language Models to access and perform sophisticated GIS operations. It bridges AI assistants with Python geospatial libraries such as Shapely, GeoPandas, PyProj, Rasterio, and PySAL. The server supports a wide range of spatial analysis, coordinate transformations, raster and vector data processing, and geospatial intelligence tasks. By integrating with MCP-compatible clients, it enhances AI tools with precise and extensible spatial capabilities.

70 21 MCP

12

Kibela MCP Server

MCP server for seamless LLM integration with Kibela knowledge management.

Kibela MCP Server enables integration of Large Language Models (LLMs) with the Kibela note-sharing platform via the Model Context Protocol. It provides search, retrieval, and management of Kibela notes, users, groups, and folders, exposing these capabilities in a standardized MCP interface. The implementation utilizes Kibela's GraphQL API and supports configuration through environment variables and Docker. Designed for interoperability with tools like Cursor, it streamlines access and manipulation of organizational knowledge by AI systems.

7 6 MCP

13

metoro-mcp-server

Bridge Kubernetes observability data to LLMs via the Model Context Protocol.

Metoro MCP Server is an implementation of the Model Context Protocol (MCP) that enables seamless integration between Kubernetes observability data and large language models. It connects Metoro’s eBPF-based telemetry APIs to LLM applications such as the Claude Desktop App, allowing AI systems to query and analyze Kubernetes clusters. This solution supports both authenticated and demo modes for accessing real-time cluster insights.

45 12 MCP

14

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

15

mcp-server-rabbitmq

RabbitMQ Reference Implementation for the Model Context Protocol (MCP)

Implements a server for the Model Context Protocol (MCP) using RabbitMQ as the messaging backend. Provides a standardized approach for handling model context, enabling scalable and efficient context management for AI applications. The project has been migrated to the official Amazon MQ repository.

40 10 MCP

16

MCP-Geo

Geocoding and reverse geocoding MCP server for LLMs.

MCP-Geo provides geocoding and reverse geocoding capabilities to AI models using the Model Context Protocol, powered by the GeoPY library. It offers various tools such as address lookup, reverse lookup from coordinates, distance calculations, and batch processing of locations, all accessible via standard MCP tool interfaces. Safety features like rate limiting and robust error handling ensure reliable and compliant usage of geocoding services. The server is compatible with environments like Claude Desktop and can be easily configured elsewhere.

28 4 MCP

17

Rember MCP

Let Claude create and manage flashcards from your chats and PDFs using Rember's spaced repetition.

Rember MCP enables integration between Claude and the Rember platform using the official Model Context Protocol (MCP). It allows users to generate flashcards from conversations or PDF documents and manage them with Rember's spaced repetition system. The tool can be run as a local MCP server which is easily configurable within Claude Desktop. It emphasizes effective tool descriptions, user guidance, and robust error handling strategies.

57 7 MCP

18

JSON MCP Filter

MCP server for JSON schema generation, smart filtering, and secure chunked data extraction.

JSON MCP Filter is an MCP-compliant server offering robust JSON schema generation and field-level filtering tools for both local files and remote HTTP/HTTPS endpoints. Leveraging quicktype for precise TypeScript type creation, it supports advanced features such as smart shape-based filtering, auto-chunking of large datasets, and memory-safe processing. Designed for seamless integration with popular MCP clients, it excels at extracting and preparing relevant JSON data for large language model contexts.

17 7 MCP

19

Trieve

All-in-one solution for search, recommendations, and RAG.

Trieve offers a platform for semantic search, recommendations, and retrieval-augmented generation (RAG). It supports dense vector search, typo-tolerant neural search, sub-sentence highlighting, and integrates with a variety of embedding models. Trieve can be self-hosted and features APIs for context management with LLMs, including Bring Your Own Model and managed RAG endpoints. Full documentation and SDKs are available for streamlined integration.

2,555 229 MCP

20

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

21

Membase-MCP Server

Decentralized memory layer server for AI agents using the Model Context Protocol.

Membase-MCP Server provides decentralized and persistent storage of conversation history and agent knowledge for AI agents using Unibase and the Model Context Protocol. It supports secure, traceable storage and retrieval of messages to ensure agent continuity and personalization within interactions. The server offers integration with Claude, Windsurf, Cursor, and Cline, allowing dynamic context management such as switching conversations and saving or retrieving messages. The server leverages the Unibase DA network for verifiable storage and agent data interoperability.

15 4 MCP

22

Memcord

Privacy-first, self-hosted chat memory and context management for Claude and AI applications.

Memcord serves as a self-hosted MCP (Model Context Protocol) server that enables users to securely organize, summarize, and search through their chat history with AI, especially for Claude, without compromising privacy. It offers intelligent memory management, conversation auto-summarization, deduplication, and context merging to build a searchable knowledge base across multiple conversations. Memcord also integrates seamlessly with Claude Desktop, VSCode, and supports various installation methods for flexibility.

18 5 MCP

23

mcp-server-qdrant

Official Model Context Protocol server for seamless integration with Qdrant vector search engine.

mcp-server-qdrant provides an official implementation of the Model Context Protocol for interfacing with the Qdrant vector search engine. It enables storing and retrieving contextual information, acting as a semantic memory layer for LLM-driven applications. Designed for easy integration, it supports environment-based configuration and extensibility via FastMCP. The server standardizes tool interfaces for managing and querying contextual data using Qdrant.

1,054 187 MCP

24

In Memoria

Persistent memory and instant context for AI coding assistants, integrated via MCP.

In Memoria is an MCP server that enables AI coding assistants such as Claude or Copilot to retain, recall, and provide context about codebases across sessions. It learns patterns, architecture, and conventions from user code, offering persistent intelligence that eliminates repetitive explanations and generic suggestions. Through the Model Context Protocol, it allows AI tools to perform semantic search, smart file routing, and track project-specific decisions efficiently.

94 17 MCP

25

MongoDB MCP Server

A Model Context Protocol server for enabling LLM interaction with MongoDB databases.

MongoDB MCP Server empowers language models to interface directly with MongoDB databases using the Model Context Protocol (MCP). It enables natural language querying and management of collections, documents, and indexes. Users can inspect database schemas, execute document operations, and manage indexes seamlessly. The tool integrates with clients like Claude Desktop for conversational database management.

172 33 MCP

26

MemoryMesh

A knowledge graph server for structured AI memory and context management.

MemoryMesh is a knowledge graph server designed to help AI models maintain structured, consistent memory, especially for interactive storytelling and RPG contexts. It is based on the Model Context Protocol (MCP), as explicitly stated, and retains core MCP server functionalities. By utilizing dynamic, schema-based configuration, the server enables creation and management of nodes and relationships, offering comprehensive tools for data integrity, feedback, and event tracking. MemoryMesh emphasizes flexibility, supporting both predefined and dynamic schemas for guiding AI interactions.

313 43 MCP

27

MCP MongoDB Server

A Model Context Protocol server for LLM interaction with MongoDB databases.

MCP MongoDB Server enables large language models to interact with MongoDB databases through the standardized Model Context Protocol interface. It provides schema inspection, document querying, aggregation, and write operations with intelligent ObjectId handling and flexible read-only configurations. Designed for seamless integration with tools like Claude Desktop, it offers collection completions, schema inference, and robust support for both development and production environments.

267 50 MCP

28

Weaviate MCP Server

A server implementation for the Model Context Protocol (MCP) built on Weaviate.

Weaviate MCP Server provides a backend implementation of the Model Context Protocol, enabling interaction with Weaviate for managing, inserting, and querying context objects. The server facilitates object insertion and hybrid search retrieval, supporting context-driven workflows required for LLM orchestration and memory management. It includes tools for building and running a client application, showcasing integration with Weaviate's vector database.

157 38 MCP

29

Mem0 MCP Server

Structured management of coding preferences using Mem0 and Model Context Protocol.

Mem0 MCP Server implements a Model Context Protocol-compliant server for storing, retrieving, and searching coding preferences. It integrates with Mem0 and offers tools for persistent management of code snippets, best practices, and technical documentation. The server exposes an SSE endpoint for clients like Cursor, enabling seamless access and interaction with coding context data.

506 104 MCP

30

MongoDB Lens

Natural language MongoDB access via a local MCP server.

MongoDB Lens offers a local Model Context Protocol (MCP) server that enables full-featured interaction with MongoDB databases using natural language queries through large language models. It provides tools for querying, running aggregations, schema analysis, performance optimization, and more. The server supports integration with a variety of MCP clients, making MongoDB data accessible and manageable by natural language commands. Users benefit from features such as connection aliasing, schema inference, and data protection mechanisms for sensitive operations.

191 24 MCP

31

memvid-mcp-server

A Streamable HTTP MCP Server for encoding and semantically searching video-based memory.

memvid-mcp-server provides a Model Context Protocol (MCP) compatible HTTP server that leverages memvid to encode text data into videos. It supports adding text chunks as video and performing semantic search over them using standardized MCP actions such as add_chunks and search. The server can be integrated with MCP clients via streamable HTTP and enables fast context retrieval for AI applications.

8 3 MCP

32

LINE Bot MCP Server

MCP server connecting LINE Messaging API with AI agents

Provides a Model Context Protocol (MCP) server implementation for integrating AI agents with the LINE Messaging API. Enables sending text and flex messages, accessing user profiles, and managing features like rich menus via MCP-compatible endpoints. Designed for connecting AI-driven context management with LINE Official Accounts for experimental and production scenarios.

493 86 MCP

33

PostHog MCP

Easily deploy and manage Model Context Protocol servers across multiple platforms.

PostHog MCP provides a server implementation for the Model Context Protocol, now maintained within the PostHog monorepo. It enables quick deployment for enhanced model context management across editors like Cursor, Claude, Claude Code, VS Code, and Zed. Users can install the MCP server with a single command, streamlining integration for large language model workflows. Documentation and further details are provided through official PostHog resources.

138 23 MCP

34

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

35

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

36

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

37

MCP Rubber Duck

A bridge server for querying multiple OpenAI-compatible LLMs through the Model Context Protocol.

MCP Rubber Duck acts as an MCP (Model Context Protocol) server that enables users to query and manage multiple OpenAI-compatible large language models from a unified API. It supports parallel querying of various providers, context management across sessions, failover between providers, and response caching. This tool is designed for debugging and experimentation by allowing users to receive diverse AI-driven perspectives from different model endpoints.

56 7 MCP

38

MCP-Typescribe

An MCP server for serving TypeScript API context to language models.

MCP-Typescribe is an open-source implementation of the Model Context Protocol (MCP) focused on providing LLMs with contextual, real-time access to TypeScript API documentation. It parses TypeScript (and other) definitions using TypeDoc-generated JSON and serves this information via a queryable server that supports tools used by AI coding assistants. The solution enables AI agents to dynamically explore, search, and understand unknown APIs, accelerating onboarding and supporting agentic behaviors in code generation.

45 6 MCP

39

OpenZIM MCP Server

Transforms ZIM archives into intelligent, structured knowledge engines for LLMs.

OpenZIM MCP Server provides structured, intelligent access to ZIM-format knowledge bases, enabling large language models to efficiently search, navigate, and understand content in offline archives. Dual operation modes allow support for both advanced and simple LLM integrations. It features smart navigation by namespace, context-aware discovery, intelligent search, and relationship mapping to optimize knowledge extraction and utilization.

8 2 MCP

40

Zettelkasten MCP Server

A Zettelkasten-based knowledge management system implementing the Model Context Protocol.

Zettelkasten MCP Server provides an implementation of the Zettelkasten note-taking methodology, enriched with bidirectional linking, semantic relationships, and categorization of notes. It enables creation, exploration, and synthesis of atomic knowledge using MCP for AI-assisted workflows. The system integrates with clients such as Claude and supports markdown, advanced search, and a structured prompt framework for large language models. The dual storage architecture and synchronous operation model ensure flexibility and reliability for managing personal or collaborative knowledge bases.

114 21 MCP

41

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

42

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

43

MCP Router

A Unified MCP Server Management App

MCP Router is a cross-platform desktop application designed to simplify the management of Model Context Protocol (MCP) servers. It enables users to centrally manage, organize, and monitor multiple MCP servers, both locally and remotely, with support for various connection methods. The app offers advanced context organization through Projects and Workspaces, as well as tools toggling and comprehensive logging. With a focus on privacy, all data is stored locally, and integration capabilities allow seamless connection with popular AI tools.

1,078 95 MCP

44

Redis MCP Server

Natural language interface for managing and querying Redis via the Model Context Protocol.

Redis MCP Server provides an MCP-compliant interface for agentic applications to interact with Redis using natural language commands. It enables AI-driven workflows to store, search, and manage structured or unstructured data efficiently. The server integrates seamlessly with any MCP client, supporting full Redis data structures and advanced querying. It is designed for scalable, high-performance data operations and native support for Azure authentication.

325 75 MCP

45

QA Sphere MCP Server

Model Context Protocol server enabling LLMs to interact with QA Sphere test cases

QA Sphere MCP Server provides a Model Context Protocol (MCP) integration for QA Sphere, allowing Large Language Models to interact with, discover, and summarize test cases within the QA Sphere test management system. It enables AI-powered IDEs and MCP clients to reference and manipulate QA Sphere test case data within development workflows. The solution supports quick integration into clients like Claude, Cursor, and 5ire, facilitating seamless collaboration and context sharing for AI-assisted development.

15 6 MCP

46

iMessage Query MCP Server

Securely query and analyze your iMessage history with LLMs using the Model Context Protocol.

iMessage Query MCP Server is an MCP-compliant server that provides safe access to the macOS iMessage database for Large Language Models (LLMs). Built with the FastMCP framework and imessagedb library, it enables querying, validation, and analysis of iMessage conversations, complete with proper phone number handling and permissions management. The tool integrates seamlessly with MCP clients such as Claude Desktop and CLine for VSCode, allowing for controlled retrieval of chat histories via standardized protocols. Enhanced security features and automated dependency management ensure a smooth and safe user experience.

71 13 MCP

47

Filestash

A modular, extensible file manager with robust API and LLM Model Context Protocol (MCP) integration.

Filestash is a versatile file manager that supports a wide range of backends including FTP, SFTP, WebDAV, S3, SMB, and popular cloud storage services such as Dropbox and Google Drive. It features a plugin-driven architecture and workflow engine for customization and automation and offers built-in viewers for images, music, and video. Filestash provides an API interface and explicit LLM integration via Model Context Protocol (MCP), enabling advanced file management automation and AI-driven workflows.

13,013 930 MCP

48

Slack MCP Server

A feature-rich Model Context Protocol server for integrating Slack Workspaces with AI model context management.

Slack MCP Server acts as a Model Context Protocol (MCP) server tailored for Slack Workspaces, providing flexible integration modes including Stealth and OAuth. It enables advanced functionalities such as fetching channel and thread messages, supporting direct and group messages, smart history retrieval, and robust context management for AI workflows. Communication is supported over Stdio, SSE, and HTTP transports, and the platform includes enhanced features like user information embedding and cache support. Designed for enterprise and individual use, it allows seamless context extraction and management without compromising workspace security.

903 136 MCP

49

Mastra

A TypeScript framework for building scalable AI-powered agents and applications.

Mastra is a modern TypeScript-based framework designed for developing AI-powered applications and autonomous agents. It offers model routing to integrate over 40 AI providers, a graph-based workflow engine, advanced context management, and production-ready tools for observability and evaluation. Mastra features built-in support for authoring Model Context Protocol (MCP) servers, enabling standardized exposure of agents, tools, and structured AI resources via the MCP interface.

18,189 1,276 MCP

50

iMessage MCP

MCP server enabling LLM integration with macOS iMessage data.

iMessage MCP offers a Model Context Protocol (MCP) server that facilitates seamless integration between large language models (LLMs) and macOS iMessage data. It provides robust tools for searching and managing iMessage messages, conversations, and contacts in a read-only manner. Features include message and contact search, chat listing, and context retrieval, making it suitable for conversational agents and context-aware applications. Built using Deno and designed for easy integration with applications such as Claude Desktop, it handles context management efficiently for AI models.

16 3 MCP

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