Memory & Knowledge MCP Servers

Knowledge graph-based persistent memory system. Store and retrieve contextual information.

Embeddings, vector search, document storage, and full-text search with the open-source AI application database.

Long-term memory layer for AI applications. Store and retrieve user preferences, conversation history, and entity facts with temporal reasoning and semantic search.

Personalized memory layer for AI. Automatically extract and store key information from conversations, enabling truly personalized AI assistant experiences.

High-performance vector database MCP server for AI applications. Store and query vector embeddings for semantic search, RAG pipelines, and similarity matching. Connect your AI assistant directly to your Qdrant collections.

Neo4j graph database server (schema + read/write-cypher) and graph database backed memory.

The Atlassian Remote MCP Server brings Confluence and Jira into any MCP-compatible AI assistant, IDE, or agent platform through a centrally hosted, enterprise-grade connection backed by Atlassian's Teamwork Graph. Launched in May 2025 with Anthropic as the first official partner and hosted on Cloudflare infrastructure, authentication is handled via OAuth 2.1 — no local server process to deploy or maintain. For Confluence specifically, available operations include summarizing pages and spaces, creating new pages from AI-generated content, searching across your wiki with natural language, and performing multi-step knowledge retrieval across Confluence spaces. Jira operations include creating, updating, and triaging work items, summarizing sprint state, and linking knowledge to in-flight issues. Atlassian's Teamwork Graph underpins every response — connecting people, services, knowledge, and work items into a unified context for richer AI answers. Enterprise customers at AT&T, NVIDIA, Pfizer, Booking.com, and Visa use the integration in production. Connect from Claude Desktop via Settings > Connectors, or from Claude Code with: `claude mcp add --transport http atlassian https://mcp.atlassian.com/v1/mcp`. Cursor and Windsurf users can add the remote URL directly to their MCP config.

The Obsidian MCP server connects AI assistants to your local Obsidian vault through the Obsidian Local REST API community plugin, enabling read, write, and search operations on your personal knowledge base. With 4,000+ GitHub stars, mcp-obsidian by MarkusPfundstein is the most widely adopted Obsidian MCP integration available. The server exposes seven tools: list_files_in_vault (enumerate all vault files and directories), list_files_in_dir (browse a specific folder), get_file_contents (read any note by path), search (full-text search across all vault notes), patch_content (insert text relative to a heading, block reference, or frontmatter field), append_content (add text to a new or existing note), and delete_file (remove a note or folder). Install via a single uvx command; set OBSIDIAN_API_KEY, OBSIDIAN_HOST, and OBSIDIAN_PORT environment variables (default port 27124). You must first install and enable the Obsidian Local REST API community plugin inside your vault settings — it exposes the HTTP endpoint this server bridges. Works with Claude Desktop, Cursor, Windsurf, Cline, and any MCP-compatible client. Ideal for summarizing meeting notes, searching research across hundreds of Markdown files, drafting new pages from AI output, or building second-brain workflows where Claude reads and writes your full knowledge base.

The Roam Research MCP Server is the official, first-party Model Context Protocol server for Roam Research, published by the Roam Research team itself and covering the full read/write surface of your Roam graph. It connects to Roam's local HTTP API, which runs inside the Roam desktop app (not the web version) — if Roam isn't open when a tool is called, the server automatically launches it via deep link and retries. Setup runs through an interactive `connect` flow (`npx @roam-research/roam-mcp connect`) that walks you through selecting a graph, choosing an access level (full, read-append, or read-only), and approving a local API token inside Roam's Settings > Graph > Local API Tokens screen; a non-interactive flag-based mode is also available for scripted or agent-driven setup. Multiple graphs can be connected simultaneously, each addressable by a short nickname. The tool surface spans six areas: graph management (list_graphs, setup_new_graph), graph guidelines (get_graph_guidelines reads a special `[[roam/agent guidelines]]` page for user-defined AI instructions), content mutation (create/update/delete for pages and blocks, append_to_daily_note, move_block, add_comment/get_comments), read/search (search, roam_query for `{{query:}}` blocks, datalog_query for raw Datomic queries, get_page, get_block, get_backlinks), navigation (get_open_windows, get_selection, open_main_window, open_sidebar), and file handling (file_get/file_upload/file_delete, including encrypted-graph decryption). The README flags this as alpha software and explicitly warns that write operations are difficult or impossible to fully undo since Roam lacks bulk-operation undo history — back up your graph before granting full write access. A companion CLI (`@roam-research/roam-cli`) is available for terminal-driven graph interaction outside an MCP client. Works with Claude Desktop, Claude Code, Cursor, and any MCP-compatible client. Ideal for daily-note capture, backlink-driven knowledge retrieval, and agent-assisted graph restructuring for second-brain / networked-note workflows.

Ingest anything from Slack to Gmail to podcast feeds, web crawling, into a searchable project.

Production-ready RAG out of the box to search and retrieve data from your own documents.

RAG Search over your content powered by Inkeep.

AI assistants interact with Anytype - a local and collaborative wiki - through natural language.

Official MCP Server to integrate with GROWI APIs.

Connect LangChain-powered workflows to MCP clients. Access vectorstores, chains, and agents built with LangChain through standardized MCP tooling.

Multi-model graph and document database MCP server. Query ArangoDB with AQL, traverse graphs, and manage collections with natural language.

Data framework for LLM applications. Index documents, build RAG pipelines, query knowledge bases, and create multi-step agents over structured and unstructured data.

Query and update your Logseq knowledge graph. Read journal entries, search notes, add blocks, manage tasks, and navigate linked thought networks via AI.

Hierarchical note-taking and knowledge management MCP. Add nodes, manage supertags, query workspaces, and automate structured information capture in Tana.

Beautiful note-taking and document creation MCP for Craft. Create and update documents, manage spaces, and access structured writing from AI tools.

Visual learning and research platform MCP. Access whiteboards, cards, and journals in Heptabase. Ideal for structuring complex research and learning projects.

Open-source Notion + Miro alternative MCP. Manage docs, whiteboards, and databases in AFFiNE. Full local-first with real-time collaboration support.

Knowledge graph-based memory for AI systems. Build structured knowledge from unstructured data, query entity relationships, and enhance AI with persistent context.

Fully managed RAG-as-a-service MCP. Index documents, PDFs, and data sources. Query knowledge bases with semantic search and structured extraction.

AI-powered memory system. Save and retrieve anything — web content, thoughts, documents — and query your personal knowledge base with natural language.

Networked note-taking MCP for Reflect. Create notes, manage backlinks, search your knowledge graph, and capture meeting notes with AI-powered linking.

Search and retrieve Wikipedia articles via MCP. Fetch article summaries, full content, infoboxes, and categories. Access multilingual Wikipedia content.

Read and write Apple Notes on macOS via MCP. Search notes, create new entries, access folders, and integrate your Notes database with AI workflows.

Access your Readwise highlights, books, articles, and reading progress through your AI assistant. Search highlights, export notes, and surface saved content for AI-powered review and synthesis.

AI-native vector database MCP server. Store and query embeddings at scale, perform semantic search, manage vector indexes, and build RAG pipelines using LanceDB's columnar storage engine.

AI-native vector database MCP integration. Perform semantic search, manage vector collections, import objects, and run GraphQL queries on your Weaviate instance from any MCP-compatible AI assistant.

Read and write Obsidian markdown notes, search across vaults, create and edit files, manage tags and backlinks. Integrates AI into your personal knowledge base.

Query and manage Logseq knowledge graphs. Search pages, create journal entries, manage tasks, traverse bi-directional links, and build knowledge graphs with AI.

Read and write Roam Research notes and databases. Query bi-directional links, create daily notes, manage blocks, and leverage Roam's graph structure with AI assistance.

Read, search, and create documents in Outline (the open-source wiki). Query collections, manage team documentation, and integrate AI into your knowledge base.

Manage AppFlowy workspaces, documents, and databases. The open-source Notion alternative with AI integration — search docs, create content, and manage tasks.

Deploy stateful AI agents with persistent memory using Letta (formerly MemGPT). Manage agent memory, create personas, and build multi-agent systems that remember across sessions.

Integrate with Guru knowledge management platform via MCP. Search and retrieve verified company knowledge cards, access team collections, sync FAQ content, create and update knowledge articles, manage expert assignments, and embed Guru knowledge into workflows for customer support and sales teams.

Connect to Slab team knowledge base via MCP. Search posts, access topic hierarchies, retrieve documentation content, create and update articles, manage post permissions, and sync company knowledge with integrations for Slack, Google Drive, GitHub, and Jira for unified team wikis.

Use Nuclino team wiki and knowledge base via MCP. Access workspaces, items, and collections. Create and edit documentation with real-time collaboration, embed visual boards and graphs, organize knowledge hierarchies, and search across all team content for fast knowledge retrieval.

Connect to Document360 knowledge base platform via MCP. Access project documentation, API references, and help center articles. Create and update documentation versions, manage categories and sections, handle team permissions, and sync knowledge with AI-powered search for SaaS product teams.

AnythingLLM private AI workspace MCP — manage workspaces, ingest documents, query embedded knowledge bases, configure LLM providers, and build custom AI agents with your own data in a self-hosted environment.

Dendron hierarchical note-taking MCP — search and navigate your Dendron vault, query notes by hierarchy or tag, look up linked references, manage schemas, and interact with your personal knowledge management system.

Capacities object-based note-taking MCP — search and create notes, manage objects (books, people, places), query linked references, access your personal knowledge graph, and organize information by type.

Supernotes collaborative note-taking MCP — search and create notecards, manage collections, query by tag or keyword, link related cards, and interact with your interconnected knowledge base.

Reflect networked note-taking MCP — search notes, capture new thoughts, navigate backlinks and forward links, query your knowledge graph, and interact with your daily notes and linked reference graph.

BookStack open-source documentation platform MCP — search and read pages across books and chapters, create and update content, manage shelves and book hierarchies, retrieve page history and attachments, and query your self-hosted wiki for AI-assisted knowledge retrieval.

Tettra internal knowledge management MCP — search company wiki pages, retrieve procedure and policy documents, query Q&A entries, manage categories and suggested edits, and surface institutional knowledge from your Tettra workspace for AI-powered team assistance.

This is the same official pinecone-io/pinecone-mcp server viewed through its RAG-pipeline and production-index angle. Beyond documentation search, teams use it to script batch upserts of embeddings into Pinecone indexes, run similarity queries with metadata filters and namespace scoping to test retrieval quality for a RAG application, and manage serverless vs. pod-based index configuration directly from an AI coding assistant — useful when iterating on chunking strategy, embedding model choice, or reranking logic without leaving the editor. Supports namespaces for multi-tenant applications and metadata filtering for hybrid structured/vector search. Install with `npx -y @pinecone-database/mcp` and a `PINECONE_API_KEY` from the Pinecone console (Node.js 18+ required); documentation-search tools work even without a key, but index read/write requires one. Maintained directly by Pinecone at 70+ GitHub stars.

Open-source embedding database for AI applications. Store and query embeddings with metadata filtering for RAG workflows. Supports multiple embedding functions and runs locally or in the cloud.

High-performance vector database for billion-scale similarity search via Milvus MCP. Manage collections, insert vectors, run ANN search, and build production RAG systems with hybrid search combining dense and sparse vectors.

Intelligent memory layer for AI applications. Automatically extracts, stores, and retrieves relevant memories across conversations. Enables personalized AI experiences with user-specific context that persists across sessions.

Long-term memory for AI agents and chatbots via Zep's API. Automatically summarizes, embeds, and retrieves conversation history. Supports entity extraction, fact-based recall, and temporal reasoning for stateful AI apps.

Trusted RAG platform for enterprise AI. Ingest documents, query corpora, and build grounded AI applications with Vectara's Boomerang embedding model. Includes hallucination detection and factual consistency scoring.

Omnivore read-it-later MCP server. Save and search articles, manage labels, query highlights and notes, and interact with your reading library using Omnivore's GraphQL API.

MCP server for listing and retrieving content from multiple knowledge bases, enabling AI assistants to search structured documentation.

The Memory Bank MCP server turns the Cline Memory Bank pattern into a centralized remote service accessible from any MCP client. Instead of storing project context in local files that get lost between sessions, this server exposes a structured multi-project memory system over the MCP protocol — read, write, update, and list memory bank files across isolated project directories. It enforces consistent file structure (projectBrief, activeContext, progress, systemPatterns, techContext, codebaseContext), prevents path traversal with strict validation, and keeps each project's context cleanly separated. Works seamlessly with Cline, Roo Code, Cursor, Windsurf, and Claude Desktop. Configure via the MEMORY_BANK_ROOT environment variable pointing to your central storage directory. Install with a single npx command; no backend infrastructure required beyond a shared filesystem. With 900+ GitHub stars and active community adoption, Memory Bank MCP is the standard for persistent AI coding context across sessions and IDE switches.