Agentic Long-Term Memory with Notion Integration alternatives

1

Notion MCP Server

Enable LLMs to interact with Notion using the Model Context Protocol.

Notion MCP Server allows large language models to interface with Notion workspaces through a Model Context Protocol server, supporting both data retrieval and editing capabilities. It includes experimental Markdown conversion to optimize token usage for more efficient communication with LLMs. The server can be configured with environment variables and controlled for specific tool access. Integration with applications like Claude Desktop is supported for seamless automation.

834 154 MCP

2

Jotdown

MCP Server for Notion Page Creation and mdBook Generation

Jotdown is an MCP server enabling large language models to interact seamlessly with Notion and generate markdown books (mdBooks). It allows LLMs to create or update Notion pages and manage the entire process of markdown book creation, including structure and navigation. Leveraging the Model Context Protocol, it provides tools for consistent and intelligent context handling between LLMs and external content platforms.

19 4 MCP

3

Klavis

One MCP server for AI agents to handle thousands of tools.

Klavis provides an MCP (Model Context Protocol) server with over 100 prebuilt integrations for AI agents, enabling seamless connectivity with various tools and services. It offers both cloud-hosted and self-hosted deployment options and includes out-of-the-box OAuth support for secure authentication. Klavis is designed to act as an intelligent connector, streamlining workflow automation and enhancing agent capability through standardized context management.

5,447 500 MCP

4

Think MCP Tool

Structured reasoning for agentic AI with the 'think' tool via Model Context Protocol.

Think MCP Tool provides an MCP (Model Context Protocol) server implementing the 'think' tool for structured reasoning in agentic AI workflows. Inspired by Anthropic's research, it enables AI agents to pause and explicitly record thoughts during complex, multi-step problem solving without altering the environment. The system enhances sequential decision-making, policy compliance, and tool output analysis, and offers advanced extensions for criticism, planning, and searching. Suitable for integration with Claude or other agentic large language models.

80 13 MCP

5

Notion MCP Integration

Integrate your minimal Notion todo list with Claude via Model Context Protocol.

Notion MCP Integration provides a simple MCP server that enables users to manage a minimalist Notion todo list through Claude, leveraging Notion's API. It supports adding, viewing, and completing tasks according to a specific Notion database structure. Designed for personal use, it allows users to interact with their tasks using natural language through Claude Desktop. The tool is easily customizable for different Notion databases by modifying the server implementation.

202 54 MCP

6

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

7

TickTick MCP Server

Enable powerful AI-driven task management for TickTick via the Model Context Protocol.

TickTick MCP Server provides comprehensive programmatic access to TickTick task management features using the Model Context Protocol. Built on the ticktick-py library, it enables AI assistants and MCP-compatible applications to create, update, retrieve, and filter tasks with improved precision and flexibility. The server supports advanced filtering, project and tag management, subtask handling, and robust context management for seamless AI integration.

35 9 MCP

8

TickTick MCP

MCP server for AI-powered TickTick task management integration

TickTick MCP is a Model Context Protocol (MCP) server that enables standardized integration of TickTick's task management features with AI assistants and developer applications. It allows programmatic access to create, update, retrieve, complete, or delete tasks and projects in TickTick via Python. Using this MCP server, AI systems can leverage TickTick's API to help automate and manage user's to-do lists and projects through natural language or other interfaces.

6 6 MCP

9

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

10

@growi/mcp-server

Bridge GROWI wiki content to AI models with context-aware access and management.

@growi/mcp-server acts as a Model Context Protocol (MCP) server that enables AI models to access, search, and manage GROWI wiki content within an organization. It facilitates seamless connection between multiple GROWI instances and language models, enhancing information retrieval and knowledge management capabilities. The platform provides comprehensive tools for page, tag, comment, and revision management as well as share link and user activity tracking. Its flexible configuration allows simultaneous operation with several GROWI apps for scalable deployment.

10 7 MCP

11

MCP Linear

MCP server for AI-driven control of Linear project management.

MCP Linear is a Model Context Protocol (MCP) server implementation that enables AI assistants to interact with the Linear project management platform. It provides a bridge between AI systems and the Linear GraphQL API, allowing the retrieval and management of issues, projects, teams, and more. With MCP Linear, users can create, update, assign, and comment on Linear issues, as well as manage project and team structures directly through AI interfaces. The tool supports seamless integration via Smithery and can be configured for various AI clients like Cursor and Claude Desktop.

117 23 MCP

12

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

13

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

14

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

15

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

16

Neo4j MCP Clients & Servers

Seamless natural language and knowledge graph integration for Neo4j via Model Context Protocol.

Neo4j MCP Clients & Servers provide standardized interfaces that enable large language models and AI assistants to interact with Neo4j databases and cloud services using natural language through the Model Context Protocol (MCP). It includes multiple servers for translating natural language to Cypher queries, managing graph memory, handling Neo4j Aura cloud services, and supporting interactive data modeling. Multiple transport modes such as STDIO, HTTP, and SSE offer flexibility for various deployments including cloud and local environments.

797 209 MCP

17

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

18

notion-mcp

An MCP server for managing Notion to-do lists via API integration.

notion-mcp provides a Model Context Protocol (MCP) server that connects with Notion's API to help users manage their personal to-do lists. It enables querying, adding, and updating tasks directly from Notion through a standardized MCP interface, and is designed for integration with tools like Claude Desktop. The project is set up for easy deployment via Smithery and supports OAuth credentials and per-user configuration.

27 4 MCP

19

Taskade MCP

Tools and server for Model Context Protocol workflows and agent integration

Taskade MCP provides an official server and tools to implement and interact with the Model Context Protocol (MCP), enabling seamless connectivity between Taskade’s API and MCP-compatible clients such as Claude or Cursor. It includes utilities for generating MCP tools from any OpenAPI schema and supports the deployment of autonomous agents, workflow automation, and real-time collaboration. The platform promotes extensibility by supporting integration via API, OpenAPI, and MCP, making it easier to build and connect agentic systems.

90 20 MCP

20

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

21

Agent-MCP

Multi-Agent Collaboration Protocol for Coordinated AI Software Development

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

1,021 124 MCP

22

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

23

Multi-Database MCP Server (by Legion AI)

Unified multi-database access and AI interaction server with MCP integration.

Multi-Database MCP Server enables seamless access and querying of diverse databases via a unified API, with native support for the Model Context Protocol (MCP). It supports popular databases such as PostgreSQL, MySQL, SQL Server, and more, and is built for integration with AI assistants and agents. Leveraging the MCP Python SDK, it exposes databases as resources, tools, and prompts for intelligent, context-aware interactions, while delivering zero-configuration schema discovery and secure credential management.

76 19 MCP

24

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

25

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

26

VideoDB Agent Toolkit

AI Agent toolkit that exposes VideoDB context to LLMs with MCP support

VideoDB Agent Toolkit provides tools for exposing VideoDB context to large language models (LLMs) and agents, enabling integration with AI-driven IDEs and chat agents. It automates context generation, metadata management, and discoverability by offering structured context files like llms.txt and llms-full.txt, and standardized access via the Model Context Protocol (MCP). The toolkit ensures synchronization of SDK versions, comprehensive documentation, and best practices for seamless AI-powered workflows.

43 8 MCP

27

ApeRAG

Hybrid RAG platform with MCP integration for intelligent knowledge management

ApeRAG is a production-ready Retrieval-Augmented Generation (RAG) platform that integrates graph-based, vector, and full-text search capabilities. It enables the construction of knowledge graphs and supports MCP (Model Context Protocol), allowing AI assistants direct interaction with knowledge bases. Features include advanced document parsing, multimodal processing, intelligent agent workflows, and enterprise management tools. Deployment is streamlined via Docker and Kubernetes, with extensive support for customization and scalability.

920 96 MCP

28

Kanboard MCP Server

MCP server for seamless AI integration with Kanboard project management.

Kanboard MCP Server is a Go-based server implementing the Model Context Protocol (MCP) for integrating AI assistants with the Kanboard project management system. It enables users to manage projects, tasks, users, and workflows in Kanboard directly via natural language commands through compatible AI tools. With built-in support for secure authentication and high performance, it facilitates streamlined project operations between Kanboard and AI-powered clients like Cursor or Claude Desktop. The server is configurable and designed for compatibility with MCP standards.

15 4 MCP

29

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

30

nerve

The Simple Agent Development Kit for LLM-based automation with native MCP support

Nerve provides a platform for building, running, evaluating, and orchestrating large language model (LLM) agents using declarative YAML configurations. It supports both client and server roles for the Model Context Protocol (MCP), allowing seamless integration, team collaboration, and advanced agent orchestration. With extensible tool support, benchmarking, and LLM-agnostic handling via LiteLLM, it enables programmable and reproducible workflows for technical users.

1,278 109 MCP

31

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

32

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

33

Aiven MCP Server

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

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

11 11 MCP

34

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

35

magg

Meta-MCP aggregator and manager for LLM capability extension.

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

62 14 MCP

36

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

37

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

38

mindsdb

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

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

35,487 5,735 MCP

39

Agentset MCP

Open-source MCP server for Retrieval-Augmented Generation (RAG) document applications.

Agentset MCP provides a Model Context Protocol (MCP) server designed to power context-aware, document-based applications using Retrieval-Augmented Generation. It enables developers to rapidly integrate intelligent context retrieval into their workflows and supports integration with AI platforms such as Claude. The server is easily installable via major JavaScript package managers and supports environment configuration for namespaces, tenant IDs, and tool descriptions.

22 10 MCP

40

MCP Toolbox for Databases

Open source MCP server for secure and efficient Gen AI database integrations.

MCP Toolbox for Databases is an open source server that implements the Model Context Protocol (MCP) for database interactions in Gen AI workflows. It manages core complexities such as connection pooling, authentication, and tool integration, enabling developers to create and deploy database tools with ease and enhanced security. The toolbox supports streamlined connections between development environments and databases, offering observability, context-aware code generation, and automation features. Its design emphasizes rapid integration, reusable tools, and compatibility with AI assistants.

11,412 988 MCP

41

dbt MCP Server

Bridge dbt projects and AI agents with rich project context.

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

420 90 MCP

42

Shrimp Task Manager

Intelligent task management for AI-powered development workflows.

Shrimp Task Manager is an MCP (Model Context Protocol) server designed to enhance AI-driven software development by persisting project context, breaking down complex tasks, and guiding structured workflows. It integrates with MCP-compatible clients such as Claude Code to maintain task memory across sessions and streamline planning and execution. The system enables persistent memory, context preservation, and automated task decomposition, helping AI models work more efficiently and effectively within project constraints.

1,868 230 MCP

43

Teamwork MCP Server

Seamless Teamwork.com integration for Large Language Models via the Model Context Protocol

Teamwork MCP Server is an implementation of the Model Context Protocol (MCP) that enables Large Language Models to interact securely and programmatically with Teamwork.com. It offers standardized interfaces, including HTTP and STDIO, allowing AI agents to perform various project management operations. The server supports multiple authentication methods, an extensible toolset architecture, and is designed for production deployments. It provides read-only capability for safe integrations and robust observability features.

11 9 MCP

44

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

45

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

46

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

47

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

48

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

49

Multi Database MCP Server

A unified server for structured, multi-database access via the Model Context Protocol.

Multi Database MCP Server provides a standardized interface for AI assistants to access and manage multiple databases concurrently through the Model Context Protocol. It supports automatic tool generation for SQL queries, transactions, schema exploration, and performance analysis for each connected database. Built using Clean Architecture, it is fully compatible with OpenAI Agents SDK, enabling seamless integration. The platform simplifies configuration and interaction with MySQL and PostgreSQL databases in a robust, modular environment.

304 49 MCP

50

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

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