mcp-server-qdrant alternatives

1

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

2

MyMCP Server (All-in-One Model Context Protocol)

Powerful and extensible Model Context Protocol server with developer and productivity integrations.

MyMCP Server is a robust Model Context Protocol (MCP) server implementation that integrates with services like GitLab, Jira, Confluence, YouTube, Google Workspace, and more. It provides AI-powered search, contextual tool execution, and workflow automation for development and productivity tasks. The system supports extensive configuration and enables selective activation of grouped toolsets for various environments. Installation and deployment are streamlined, with both automated and manual setup options available.

93 9 MCP

3

Vectorize MCP Server

MCP server for advanced vector retrieval and text extraction with Vectorize integration.

Vectorize MCP Server is an implementation of the Model Context Protocol (MCP) that integrates with the Vectorize platform to enable advanced vector retrieval and text extraction. It supports seamless installation and integration within development environments such as VS Code. The server is configurable through environment variables or JSON configuration files and is suitable for use in collaborative and individual workflows requiring vector-based context management for models.

97 21 MCP

4

RAG Documentation MCP Server

Vector-based documentation search and context augmentation for AI assistants

RAG Documentation MCP Server provides vector-based search and retrieval tools for documentation, enabling large language models to reference relevant context in their responses. It supports managing multiple documentation sources, semantic search, and real-time context delivery. Documentation can be indexed, searched, and managed with queueing and processing features, making it highly suitable for AI-driven assistants. Integration with Claude Desktop and support for Qdrant vector databases is also available.

238 29 MCP

5

Memory MCP

A Model Context Protocol server for managing LLM conversation memories with intelligent context window caching.

Memory MCP provides a Model Context Protocol (MCP) server for logging, retrieving, and managing memories from large language model (LLM) conversations. It offers features such as context window caching, relevance scoring, and tag-based context retrieval, leveraging MongoDB for persistent storage. The system is designed to efficiently archive, score, and summarize conversational context, supporting external orchestration and advanced memory management tools. This enables seamless handling of conversation history and dynamic context for enhanced LLM applications.

10 6 MCP

6

mcp-pinecone

A Pinecone-backed Model Context Protocol server for semantic search and document management.

mcp-pinecone implements a Model Context Protocol (MCP) server that integrates with Pinecone indexes for use with clients such as Claude Desktop. It provides powerful tools for semantic search, document reading, listing, and processing within a Pinecone vector database. The server supports operations like embedding, chunking, and upserting records, enabling contextual management of large document sets. Designed for ease of installation and interoperability via the MCP standard.

150 35 MCP

7

MCP Local RAG

Privacy-first local semantic document search server for MCP clients.

MCP Local RAG is a privacy-preserving, local document search server designed for use with Model Context Protocol (MCP) clients such as Cursor, Codex, and Claude Code. It enables users to ingest and semantically search local documents without using external APIs or cloud services. All processing, including embedding generation and vector storage, is performed on the user's machine. The tool supports document ingestion, semantic search, file management, file deletion, and system status reporting through MCP.

10 3 MCP

8

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

9

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

10

@dealx/mcp-server

MCP server enabling LLMs to search and interact with the DealX platform.

Implements the Model Context Protocol, providing a standardized interface for large language models to interact with the DealX platform. Supports searching for ads through structured prompts and is designed for easy integration with tools like Claude and VS Code extensions. Flexible configuration options are available for environment variables, logging, and deployment. Extensible architecture supports future feature additions beyond ad search.

0 2 MCP

11

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

12

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

13

Google Workspace MCP Server

Full natural language control of Google Workspace through the Model Context Protocol.

Google Workspace MCP Server enables comprehensive natural language interaction with Google services such as Calendar, Drive, Gmail, Docs, Sheets, Slides, Forms, Tasks, and Chat via any MCP-compatible client or AI assistant. It supports both single-user and secure multi-user OAuth 2.1 authentication, providing a production-ready backend for custom apps. Built on FastMCP, it delivers high performance and advanced context handling, offering deep integration with the entire Google Workspace suite.

890 259 MCP

14

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

15

Ragie Model Context Protocol Server

Seamless knowledge base retrieval via Model Context Protocol for enhanced AI context.

Ragie Model Context Protocol Server enables AI models to access and retrieve information from a Ragie-managed knowledge base using the standardized Model Context Protocol (MCP). It provides a retrieve tool with customizable query options and supports integration with tools like Cursor and Claude Desktop. Users can configure API keys, specify partitions, and override tool descriptions. Designed for rapid setup via npx and flexible for project-specific or global usage.

81 18 MCP

16

Exa MCP Server

Fast, efficient web and code context for AI coding assistants.

Exa MCP Server provides a Model Context Protocol (MCP) server interface that connects AI assistants to Exa AI’s powerful search capabilities, including code, documentation, and web search. It enables coding agents to retrieve precise, token-efficient context from billions of sources such as GitHub, StackOverflow, and documentation sites, reducing hallucinations in coding agents. The platform supports integration with popular tools like Cursor, Claude, and VS Code through standardized MCP configuration, offering configurable access to various research and code-related tools via HTTP.

3,224 244 MCP

17

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

18

Yuque-MCP-Server

Seamless integration of Yuque knowledge base with Model-Context-Protocol for AI model context management.

Yuque-MCP-Server provides an MCP-compatible server for interacting with the Yuque knowledge base platform. It enables AI models to retrieve, manage, and analyze Yuque documents and user information through a standardized Model-Context-Protocol interface. The server supports operations such as document creation, reading, updating, deletion, advanced search, and team statistics retrieval, making it ideal for AI-powered workflows. Inspired by Figma-Context-MCP, it facilitates contextual awareness and dynamic knowledge management for AI applications.

31 13 MCP

19

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

20

MCP Language Server

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

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

1,256 94 MCP

21

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

22

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

23

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

24

mcp-local-rag

Local RAG server for web search and context injection using Model Context Protocol.

mcp-local-rag is a local server implementing the Model Context Protocol (MCP) to provide retrieval-augmented generation (RAG) capabilities. It performs live web search, extracts relevant context using Google's MediaPipe Text Embedder, and supplies the information to large language models (LLMs) for enhanced, up-to-date responses. The tool is designed for easy local deployment, requiring no external APIs, and is compatible with multiple MCP clients. Security audits are available, and integration is demonstrated across several LLM platforms.

89 18 MCP

25

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

26

Semgrep MCP Server

A Model Context Protocol server powered by Semgrep for seamless code analysis integration.

Semgrep MCP Server implements the Model Context Protocol (MCP) to enable efficient and standardized communication for code analysis tasks. It facilitates integration with platforms like LM Studio, Cursor, and Visual Studio Code, providing both Docker and Python (PyPI) deployment options. The tool is now maintained in the main Semgrep repository with continued updates, enhancing compatibility and support across developer tools.

611 54 MCP

27

OpenAI WebSearch MCP Server

Intelligent web search with OpenAI reasoning model support, fully MCP-compatible.

OpenAI WebSearch MCP Server provides advanced web search functionality integrated with OpenAI's latest reasoning models, such as gpt-5 and o3-series. It features full compatibility with the Model Context Protocol, enabling easy integration into AI assistants that require up-to-date information and contextual awareness. Built with flexible configuration options, smart reasoning effort controls, and support for location-based search customization. Suitable for environments such as Claude Desktop, Cursor, and automated research workflows.

75 18 MCP

28

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

29

Naver Search MCP Server

Unified Naver Search and DataLab API integration for context-aware tools.

Naver Search MCP Server provides a Model Context Protocol (MCP) compliant server that integrates Naver Search and DataLab APIs. It enables easy and comprehensive search across a wide range of Naver services, as well as advanced trend analysis with context-aware tools. The implementation supports Smithery platform installation, temporal context handling, and offers tools for both information retrieval and data analytics within the Naver ecosystem.

45 20 MCP

30

Yandex Tracker MCP Server

A Model Context Protocol server for secure and flexible integration with Yandex Tracker APIs.

Yandex Tracker MCP Server enables AI assistants to securely interact with Yandex Tracker APIs by providing authenticated access to issues, queues, comments, worklogs, and more. It supports advanced query capabilities, optional Redis caching for enhanced performance, and multiple transport options including HTTP and stdio. The server features OAuth 2.0 authentication, granular security controls, and can be seamlessly integrated as an extension in various AI clients, such as Claude Desktop.

28 6 MCP

31

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

32

TeslaMate MCP Server

Query your TeslaMate data using the Model Context Protocol

TeslaMate MCP Server implements the Model Context Protocol to enable AI assistants and clients to securely access and query Tesla vehicle data, statistics, and analytics from a TeslaMate PostgreSQL database. The server exposes a suite of tools for retrieving vehicle status, driving history, charging sessions, battery health, and more using standardized MCP endpoints. It supports local and Docker deployments, includes bearer token authentication, and is intended for integration with MCP-compatible AI systems like Claude Desktop.

106 14 MCP

33

Sourcerer MCP

Semantic code search & navigation MCP server for efficient AI agent context retrieval.

Sourcerer MCP provides a Model Context Protocol (MCP) server that enables AI agents to perform semantic code search and navigation. By indexing codebases at the function, class, and chunk level, it allows agents to retrieve only the necessary code snippets, greatly reducing token consumption. The tool integrates with Tree-sitter for language parsing and OpenAI for generating code embeddings, supporting advanced contextual code understanding without full file ingestion.

95 11 MCP

34

MCP-searxng

MCP server bridging agentic systems with SearXNG web search

MCP-searxng enables agentic systems to interface with web search engines via the SearXNG platform by implementing the Model Context Protocol. It supports both command-line and local server deployment, providing flexible integration options. Users can configure custom SearXNG server URLs and connect through clients like uvx or claude desktop. The tool simplifies access to structured web search within agentic workflows.

107 19 MCP

35

Everything Search MCP Server

Fast, cross-platform file search via Model Context Protocol integration.

Everything Search MCP Server provides fast file and folder search capabilities across Windows, macOS, and Linux platforms as an MCP server. It leverages native search utilities such as the Everything SDK on Windows, mdfind on macOS, and locate/plocate on Linux. The tool exposes a standardized search interface with customizable parameters including query, sorting, and matching options. It is suitable for integration with AI clients or automation tools that follow the Model Context Protocol.

268 35 MCP

36

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

37

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

38

tavily-search MCP server

A search server that integrates Tavily API with Model Context Protocol tools.

tavily-search MCP server provides an MCP-compliant server to perform search queries using the Tavily API. It returns search results in text format, including AI responses, URLs, and result titles. The server is designed for easy integration with clients like Claude Desktop or Cursor and supports both local and Docker-based deployment. It facilitates AI workflows by offering search functionality as part of a standardized protocol interface.

44 11 MCP

39

Driflyte MCP Server

Bridging AI assistants with deep, topic-aware knowledge from web and code sources.

Driflyte MCP Server acts as a bridge between AI-powered assistants and diverse, topic-aware content sources by exposing a Model Context Protocol (MCP) server. It enables retrieval-augmented generation workflows by crawling, indexing, and serving topic-specific documents from web pages and GitHub repositories. The system is extensible, with planned support for additional knowledge sources, and is designed for easy integration with popular AI tools such as ChatGPT, Claude, and VS Code.

9 2 MCP

40

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

41

box-mcp-server

Expose your Box files to AI with a Model Context Protocol server.

box-mcp-server lets users connect their Box accounts to AI applications via the Model Context Protocol (MCP). It securely authenticates to Box with enterprise credentials or developer tokens and serves file search and reading capabilities to downstream clients. Designed for use with Claude Desktop and the MCP Inspector, it provides seamless integration of Box documents into AI workflows.

10 11 MCP

42

Quarkus Model Context Protocol Servers

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

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

176 46 MCP

43

CVE-Search MCP Server

MCP server for querying and managing CVE-Search vulnerability data.

CVE-Search MCP Server implements the Model Context Protocol to provide structured access to the CVE-Search API. It enables querying vendors, products, and vulnerabilities, as well as retrieving detailed information for specific CVEs. The server facilitates model context integration via MCP client tools, supporting seamless interactions for vulnerability data management.

67 11 MCP

44

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

45

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

46

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

47

Snowflake Cortex AI Model Context Protocol (MCP) Server

Tooling and orchestration for Snowflake Cortex AI via Model Context Protocol.

Provides an MCP server that brings Snowflake Cortex AI, object management, and SQL orchestration to the MCP ecosystem. Enables Cortex Search, Analyst, and Agent services for structured and unstructured data querying, along with automated SQL execution and object management. Designed for integration with MCP clients to streamline AI-powered data workflows and context-sensitive operations within Snowflake environments.

176 60 MCP

48

XiYan MCP Server

A server enabling natural language queries to SQL databases via the Model Context Protocol.

XiYan MCP Server is a Model Context Protocol (MCP) compliant server that allows users to query SQL databases such as MySQL and PostgreSQL using natural language. It leverages the XiYanSQL model, providing state-of-the-art text-to-SQL translation and supports both general LLMs and local deployment for enhanced security. The server lists available database tables as resources and can read table contents, making it simple to integrate with different applications.

218 43 MCP

49

Code Declaration Lookup MCP Server

Fast, language-agnostic code declaration search and lookup server via MCP.

Provides a Model Context Protocol (MCP) server that indexes code declarations using universal ctags and SQLite with FTS5 full-text search. Offers search and listing functionality for functions, classes, structures, enums, and other code elements across any language supported by ctags. Enables seamless integration with coding agents for dynamic indexing, respects .gitignore, and supports ctags file ingestion and management.

2 1 MCP

50

Supabase MCP Server

Connect Supabase projects to AI assistants using the Model Context Protocol.

Supabase MCP Server enables direct, secure integration between Supabase projects and AI assistants such as Cursor, Claude, and Windsurf. Leveraging the Model Context Protocol, it provides standardized endpoints for external LLMs to perform tasks like managing tables, fetching configurations, and querying data on Supabase. The server supports OAuth 2.1 Dynamic Client Registration and offers easy setup with feature groups and popular client installers for local, cloud, and self-hosted environments.

2,263 253 MCP

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