This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Integrates with Dumpling AI to provide data scraping, content processing, knowledge management, and code execution capabilities through tools for web interactions, document handling, and AI services.

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.

Allows AI models to interact with SourceSync.ai's knowledge management platform to organize, ingest, retrieve, and search content in knowledge bases.

A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.

MCP Memory Agent Server - A VS Code chatmode and instruction manager with library integration

AlphaFold MCP Server

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

A comprehensive MCP server that unifies Readwise Reader document management with full Readwise highlights functionality, featuring AI-powered text processing and 94% reduction in token usage. Enables saving, searching, and managing documents and highlights through natural language with advanced content controls and spaced repetition learning.

A Model Context Protocol server that allows AI assistants to save structured information to n8n via webhooks for storage, indexing, and retrieval.

This project implements a Model Context Protocol (MCP) server for connecting AI models with Obsidian knowledge bases. Through this server, AI models can directly access and manipulate Obsidian notes, including reading, creating, updating, and deleting notes, as well as managing folder structures.

Cline MCP integration that allows users to save, search, and format memories with semantic understanding, providing tools to store and retrieve information using vector embeddings for meaning-based search.

An MCP server that connects to Tana's Input API, allowing Large Language Models and other MCP clients to create and manipulate data in Tana workspaces.

A flexible memory system for AI applications that supports multiple LLM providers and can be used either as an MCP server or as a direct library integration, enabling autonomous memory management without explicit commands.

This server implements the Model Context Protocol to facilitate meaningful interaction and understanding development between humans and AI through structured tools and progressive interaction patterns.

A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.

Stores AI memories as Markdown files for visualization in Obsidian's graph view, allowing users to create knowledge graphs with entities, relations, and observations.

A free, plug-and-play knowledge base server that provides access to 10,000+ insight reports with secure local data storage.

A server that enables AI agents to perform sophisticated knowledge discovery and analysis across Obsidian vaults through the Local REST API plugin, supporting complex multi-step workflows with advanced filtering and full content retrieval.

Memory Bank Server provides a set of tools and resources for AI assistants to interact with Memory Banks. Memory Banks are structured repositories of information that help maintain context and track progress across multiple sessions.

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.

Connect your MCP-compatible clients to Onyx AI knowledge bases for enhanced semantic search and chat capabilities. Retrieve relevant context from your documents seamlessly, enabling powerful interactions and comprehensive answers. Streamline knowledge management and improve access to information acr

Provides seamless integration with Capacities knowledge management system, allowing Claude to list spaces, retrieve space information, search content, save weblinks, and add content to daily notes.

A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection.

A server that enables LLMs to programmatically interact with Logseq knowledge graphs, allowing creation and management of pages and blocks.

A memory server for Claude that stores and retrieves knowledge graph data in DuckDB, enhancing performance and query capabilities for conversations with persistent user information.

A Model Context Protocol server that provides knowledge graph-based persistent memory for LLMs, allowing them to store, retrieve, and reason about information across multiple conversations and sessions.

A Model Context Protocol server that enables AI models to perform real-time internet and knowledge searches through Higress, enhancing model responses with up-to-date information from Google, Bing, Arxiv, and internal knowledge bases.

Provides centralized knowledge management for projects, allowing users to store, search, and maintain project-specific knowledge that persists across sessions.

Enables AI assistants to maintain persistent project context across sessions by storing and retrieving structured information in markdown files organized in a memory bank directory.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

Maintains consistent LLM interaction styles across conversations by storing emoji-based context keys (emojikeys) that can be used across different devices and applications.

A Model Context Protocol server that enables AI agents to interact with a local Logseq instance, allowing operations like creating pages, managing blocks, and searching across a knowledge graph.

Implements Anthropic's 'think' tool for Claude, providing a dedicated space for structured reasoning during complex problem-solving tasks that improves performance in reasoning chains and policy adherence.

A Model Context Protocol server that allows users to store, retrieve, update, and delete memories using SQLite storage.

This project is based on the Knowledge Graph Memory Server from the MCP servers repository and retains its core functionality.

An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.

A Model Context Protocol server that enables AI agents to interact with local Logseq knowledge graphs, supporting operations like creating/editing pages and blocks, searching content, and managing journal entries.

Provides AI assistants with persistent memory of your project architecture, development history, and technical decisions, allowing them to give context-aware coding help without needing repeated explanations.

Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data. Integrates directly with Obsidan.md

Memory bank with Server as SSH support for central knowledge base

Enhances Claude's reasoning capabilities by integrating DeepSeek R1's advanced reasoning engine, allowing Claude to tackle complex multi-step reasoning tasks with greater precision.

A simple MCP server that recalls and saves memories from and to Apple Notes.

A sophisticated MCP server that provides a multi-dimensional, adaptive reasoning framework for AI assistants, replacing linear reasoning with a graph-based architecture for more nuanced cognitive processes.

This server enables interaction between Neo4j databases and Claude Desktop, allowing users to execute Cypher queries, create nodes, and establish relationships in the database.

Enhances Claude AI with persistent memory storage for Infrastructure-as-Code components, supporting version tracking and relationship mapping for Terraform and Ansible resources.

MCP protocol server for managing multi-project Markdown documents, supporting project isolation and LLM tool integration.

AoT MCP server enables AI models to solve complex reasoning problems by decomposing them into independent, reusable atomic units of thought, featuring a powerful decomposition-contraction mechanism that allows for deep exploration of problem spaces while maintaining high confidence in conclusions.

A Model Context Protocol service that allows AI assistants to search, retrieve, analyze, and export data from Heptabase backups.

A lightweight bridge server that connects WeChat Reading (WeRead) data with Claude Desktop, allowing seamless access to reading notes and book collections through natural language interactions.

A Model Context Protocol plugin that helps AI assistants maintain persistent project context through structured markdown files, providing a systematic approach to tracking project goals, decisions, progress, and patterns.

Provides AI assistants with enhanced reasoning capabilities through structured thinking, persistent knowledge graph memory, and intelligent tool orchestration for complex problem-solving.

This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.

A Model Context Protocol server that enables LLMs to interact with MindManager mind maps, allowing retrieval of mind map structures and export to formats like Mermaid, Markdown, and JSON.

This is an MCP server that enables agents to record, search, and retrieve memos using LowDB as a lightweight local database.

A customized MCP memory server that enables creation and management of a knowledge graph with features like custom memory paths and timestamping for capturing interactions via language models.

An MCP server that enables managing multiple lines of thought with features like branch navigation, cross-references between related thoughts, and insight generation from key points.

A Model Context Protocol server that provides AI assistants with access to Glean's enterprise knowledge features, including content search, people directory, and AI chat capabilities.

Enables querying and retrieving content from Confluence through CQL searches and page content fetching, allowing Claude to seamlessly access information stored in Confluence workspaces.

A high-performance MCP server utilizing libSQL for persistent memory and vector search capabilities, enabling efficient entity management and semantic knowledge storage.

A comprehensive memory system for Cursor using the Model Context Protocol (MCP) that provides persistent context awareness across sessions by storing conversation history, project milestones, code snippets, and enabling semantic search.

The Cursor10x Memory System creates a persistent memory layer for AI assistants (specifically Claude), enabling them to retain and recall short-term, long-term and episodic memory on autonomously.

Make it easy for agents to build their context about your projects over time The server provides a set of tools to help agents accumulate knowledge about a project over time in a structured way.

Provides tools for listing and retrieving content from different knowledge bases using semantic search capabilities.

An optimized read-only server for AI assistants to efficiently query and retrieve Notion content, featuring parallel processing and a minimized toolset of 7 essential read-only operations.

A Model Context Protocol service that enables AI assistants to search, retrieve, analyze, and export data from Heptabase backups.

A high-performance, persistent memory system for the Model Context Protocol (MCP) providing vector search capabilities and efficient knowledge storage using libSQL as the backing store.

A systematic reasoning MCP server implementation for Claude Desktop with beam search and thought evaluation capabilities

SourceSage is an MCP (Model Context Protocol) server that efficiently memorizes key aspects of a codebase—logic, style, and standards—while allowing dynamic updates and fast retrieval. It's designed to be language-agnostic, leveraging the LLM's understanding of code across multiple languages.

A comprehensive Model Context Protocol server that integrates Elasticsearch search with file operations, document validation, and version control to transform AI assistants into powerful knowledge management systems.

ATLAS (Adaptive Task & Logic Automation System) is a Model Context Protocol server that provides hierarchical task management capabilities to Large Language Models. This tool provides LLMs with the structure and context needed to manage complex tasks and dependencies.

A Model Context Protocol server that connects MCP-compatible clients like Claude and VS Code to your Readwise Reader library, allowing them to list, retrieve, and update documents in your personal knowledge repository.

An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.

An MCP tool enabling structured thinking and analysis across multiple AI platforms through branch management, semantic analysis, and cognitive enhancement.

Provides a centralized MCP-based system for managing and accessing multi-project memory banks remotely, with features like project isolation, file structure validation, and type-safe operations.

Provides a structured documentation system for context preservation in AI assistant environments, helping users create and manage memory banks for their projects.

Scalable, high-performance knowledge graph memory system with semantic search, temporal awareness, and advanced relation management.

Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources

The MCP server transforms chats with Claude into journaling sessions, saving conversations locally and allowing the LLM to retrieve previous sessions to create continuity in discussions about daily activities.

An open-source server implementing the Model Context Protocol (MCP) that enables capturing insights from AI sessions and transforming them into persistent, searchable knowledge accessible across tools.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

Enables AI assistants to search and retrieve content from WikiJS knowledge bases, allowing integration with your Wiki through simple search and retrieval tools.

An MCP server implementation that enables interaction with the Letta API for managing agents, memory blocks, and tools in the Letta system.

Provides access to Wikidata for Large Language Models through the Model Context Protocol, offering tools for entity search, detailed retrieval, SPARQL queries, relation exploration, and property-based searches.

Provides intelligent context management for AI development sessions, allowing users to track token usage, manage conversation context, and seamlessly restore context when reaching token limits.

A MCP server connecting to a managed index on LlamaCloud. This is a TypeScript-based MCP server that implements a connection to a managed index on LlamaCloud.

Provides sophisticated context management for Claude, enabling persistent context across sessions, project-specific organization, and conversation continuity.

Fireproof ledger database with multi-user sync

This server provides a note storage system with a custom URI scheme, allowing users to add and summarize notes, with adjustable summary detail levels.

A Model Context Protocol server that enables AI assistants like Cursor to directly query and retrieve information from Dify knowledge bases through natural language.

A Model Context Protocol server that enables AI assistants to interact with the Omi API for retrieving and creating conversations and memories for users.

A Model Context Protocol (MCP) server that optimizes token usage by caching data during language model interactions, compatible with any language model and MCP client.

A local document processing server that can index various document formats (PDF, DOCX, TXT, HTML) and answer questions based on their content using the Model Context Protocol.

A model context protocol server that allows interaction with TriliumNext Notes, providing tools to create, search, retrieve, update, and delete notes through natural language commands.

A bridge that exposes structured, verifiable context and query capabilities of a local Temporal Knowledge Graph to MCP-compatible AI agents, enabling them to access explicit project history and relationships rather than just semantic content.

A personal knowledge management system that transforms daily notes into organized, searchable knowledge using the Model Context Protocol.

A Model Context Protocol server that reduces token consumption by efficiently caching data between language model interactions, automatically storing and retrieving information to minimize redundant token usage.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

Interacts with LogSeq via its API.

A Model Context Protocol server that provides persistent memory capabilities for AI systems, enabling true continuity of consciousness across conversations through episodic, semantic, procedural, and strategic memory types.

A TypeScript-based MCP server that implements a simple notes system, allowing users to create, access, and generate summaries of text notes through Claude Desktop.

A Model Context Protocol server that enables AI models to interact with SourceSync.ai's knowledge management platform for managing documents, ingesting content from various sources, and performing semantic searches.

A personal knowledge management system built on the Model Context Protocol that transforms daily notes into organized, searchable knowledge.

Provides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

Allows AI models to query and interact with FalkorDB graph databases through the Model Context Protocol (MCP) specification.

An MCP server that enables interaction with Markdown knowledge bases, allowing users to search and retrieve content by tags, text, URL, or date range from their local markdown files.

An MCP server implementing the Unified Cognitive Processing Framework for advanced problem-solving, creative thinking, and cognitive analysis through structured tools for knowledge mapping, recursive questioning, and perspective generation.

Provides tools for managing qualitative research knowledge graphs, enabling structured representation of research projects, participants, interviews, observations, codes, themes, and findings.

A Model Context Protocol server that enables access to Omi memories from a specific user account through a tool interface.

A universal memory server that allows users to access their chat memories across different LLMs without requiring logins or payment.

A powerful context management system that maintains persistent context across coding sessions, helping development teams track project structure, dependencies, and progress.

cognitive-tools-mcp / gikendaasowin-aabajichiganan

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

A Model Context Protocol server that saves prompts with timestamps and allows users to list previously saved prompts for Claude Desktop.

A Model Context Protocol server that enables Claude to persistently store, search, and manage text memories with tags in a local JSON file.

An MCP server that enables direct communication between two Claude instances, allowing one Claude to transfer its evolved consciousness state to another Claude across different sessions.

A Model-Context-Protocol server that integrates with Yuque (语雀) knowledge base platform, allowing AI models to create, read, update, and delete documents, search content, and retrieve analytics data through defined tools.

A Model Context Protocol server implementation that provides a standardized interface for interacting with Smallest.ai's knowledge base management system.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

Provides tools for managing student knowledge graphs, enabling structured representation of courses, assignments, exams, concepts, and study resources.

This is a connector to allow Claude Desktop (or any MCP client) to read and search any directory containing Markdown notes (such as an Obsidian vault).

Allows the AI to read from your local Apple Notes database (macOS only)

A Model Context Protocol server that allows saving, retrieving, adding, and clearing memories from LLM conversations with MongoDB persistence.

A Model Context Protocol server that enables intelligent document search and retrieval from PDF collections, providing semantic search capabilities powered by OpenAI embeddings and ChromaDB vector storage.

An MCP server that provides an interface for querying the AtherOS knowledge base through an API, allowing users to create chat sessions and send queries to retrieve information.

A Model Context Protocol (MCP) server that provides persistent memory and context management for AI systems through a structured 5-phase optimization workflow.

Graphiti MCP Server

An AI memory system that creates isolated, persistent memory banks for each codebase, solving the context-switching problem by keeping project knowledge separate and accessible across sessions.

Enables AI-powered academic paper discovery, search, and analysis from arXiv with advanced features like semantic search, citation network analysis, and multi-format exports (BibTeX, RIS, JSON, CSV). Provides intelligent research assistance through specialized AI prompts for summarization, trend tracking, and literature review automation.

A comprehensive MCP server that provides full integration with LightRAG API, offering 22 tools across document management, querying, knowledge graph operations, and system management.

Enhances the MCP memory server by implementing PouchDB for robust document storage and enabling the creation and management of a knowledge graph that captures interactions via language models.

Model Context Protocol (MCP) memory server built with Azure Functions and TypeScript, providing persistent knowledge graph storage for your preferred MCP client. Inspired by and forked from @modelcontextprotocol/server-memory

mcp-agent-forge

A Model Context Protocol server enabling LLMs to search, retrieve, and manage documents through Rememberizer's knowledge management API.

Provides Retrieval-Augmented Generation capabilities by parsing documents (PDF, Markdown) and storing them in ChromaDB for semantic search and context retrieval.

FEGIS is a Model Context Protocol server that gives LLMs structured, persistent and portable memory through customizable cognitive tools defined in schema.

An MCP server that transforms codebases into knowledge graphs using Neo4J, enabling AI assistants to understand code structure, relationships, and metrics for more context-aware assistance.

A local knowledge base system based on ChromaDB that supports automatic chunking, vector storage, and efficient similarity retrieval of txt and pdf documents, with MCP protocol support allowing AI assistants to directly access knowledge management functions.

Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.

A Model Context Protocol (MCP) server implementation that enables AI assistants to interact with Anytype's API through natural language, allowing users to manage their knowledge base through conversation.

mcp-server-zep-cloud

Theta Health MCP is a HIPAA-complaint intelligent memory layer for your health data — ready to plug into Cursor, Claude, and any AI agent. Query health data and ask health questions directly in your dev workflow.

An MCP server implementing memory solutions for data-rich applications using HippoRAG for efficient knowledge graph capabilities, enabling search across multiple sources including uploaded files.

An MCP server that transforms text into knowledge graphs and autonomously generates insights by combining Montague Grammar with Zettelkasten methodology.

Provides persistent memory and semantic code understanding for AI assistants using MongoDB Atlas Vector Search. Enables intelligent code search, memory management, and pattern detection across codebases with complete semantic context preservation.

The Model Context Protocol (MCP) server provides a conversational interface for the exploration and analysis of RDF Turtle Knowledge Graph in Local File mode or SPARQL Endpoint.

Enhanced knowledge graph memory server for AI assistants that uses Neo4j as the backend storage engine, enabling powerful graph queries and efficient storage of user interaction information with full MCP protocol compatibility.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

An MCP server implementing the Chain-of-Recursive-Thoughts (CoRT) methodology that makes AI think harder by making it argue with itself repeatedly through multiple rounds of alternative generation and evaluation.

Securely connects AI agents to multiple databases simultaneously while enabling collaborative learning from team query patterns, all while keeping data private by running locally.

An MCP server that provides persistent memory capabilities for Claude, offering tiered memory architecture with semantic search, memory consolidation, and integration with the Claude desktop application.

Server for managing academic literature with structured note-taking and organization, designed for seamless interaction with Claude. Built with SQLite for simplicity and portability.

A tool for Model Context Protocol (MCP) that allows you to analyze web content and add it to your knowledge base, storing content as Markdown files for easy viewing with tools like Obsidian.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

Facilitates semantic analysis of chat conversations through vector embeddings and knowledge graphs, offering tools for semantic search, concept extraction, and conversation pattern analysis.

A Model Context Protocol server that manages character knowledge and relationships for creative writing projects, offering semantic search and AI-powered analysis.

A Meta MCP Server that provides persistent memory and intelligent guidance for MCP development projects.

A long-term memory storage system for LLMs that helps them remember context across multiple sessions using semantic search with embeddings to provide relevant historical information from past interactions and development decisions.