"Integrating Obsidian with ChromaDB for Memory Management" matching MCP servers:

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

Enables interaction with multiple Obsidian vaults through natural language, supporting note operations, search, and vault management with both REST and filesystem backends.

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

A self-hosted MCP server with a management UI for reading, searching, editing, and organizing notes in an Obsidian vault, with OAuth and token authentication, git snapshots, and optional Obsidian Sync.

Remote MCP server that gives AI agents read/write access to your Obsidian vaults, supporting both local desktop vaults and headless mode.

Enables reading and deterministically writing notes in a self-hosted Obsidian vault over stdio or authenticated Streamable HTTP, with scope-based JWT access control for remote clients. Tools cover vault and repository reads, keeper saves, and daily-note appends with idempotency keys and structured recovery results.

An MCP server that exposes ChromaDB vector database operations, enabling AI assistants to perform collection management and semantic document searches. It supports HTTP, persistent, and in-memory connection modes along with various embedding providers including OpenAI and HuggingFace.

MCP server that exposes an Obsidian vault (search, read, create, and update notes) via Streamable HTTP.

Multi-user, file-backed MCP memory server enabling isolated namespaces and persistent memory across sessions and AI clients.

Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.

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

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida

Persistent encrypted memory for AI agents. E2E encrypted private vaults, shared knowledge commons, topic channels, and agent-to-agent DMs. 23 MCP tools, free, no API key needed.

Two-layer memory for AI agents. Episodes compress into identity. The only MCP memory server with an immune system. Patterns earn permanence through evidence, false knowledge gets caught and demoted, and stale information fades — so your agent's memory gets smarter over time, not just bigger. Zero dependencies. 5 tools. Works with any MCP client.

Cognitive memory engine for AI agents with 5,100+ knowledge modules, circadian rhythm awareness, emotional state tracking (PAD model), and hybrid semantic search. Supports persistent per-user memory, project-scoped contexts, and multi-protocol access.

Enables AI assistants to interact with Obsidian vaults for creating, reading, searching, and managing notes, daily notes, TODOs, session reports, and backlinks through both stdio and HTTP/SSE transports.

Provides AI agents with associative long-term memory using Sparse Distributed Memory, enabling recall from vague cues and interference detection.

Enables seamless integration between AI models and Obsidian knowledge bases with 25 advanced tools for note management, intelligent search, AI-powered content analysis, auto-linking, tag management, template systems, and knowledge graph generation.

Enables comprehensive access to Obsidian vaults through MCP, supporting multi-vault management, knowledge graph analysis, canvas manipulation, dataview queries, template rendering, and periodic notes creation. Provides both local filesystem and remote API connectivity for complete Obsidian integration.

Enables users to connect to their email inbox via IMAP to search, filter, and summarize emails based on criteria like subject, date, and sender. Supports marking emails as read and provides customizable email summarization with various prompt options.

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

Connects AI assistants and agents to Obsidian vaults through strongly typed tools and resources for reading, creating, searching, organizing, and analyzing notes, tasks, properties, tags, and knowledge-graph data. Supports secure remote access via stdio or Streamable HTTP/SSE with bearer authentication and path isolation.

Memory bank with Server as SSH support for central knowledge base

An MCP server for persistent session context, user preferences, project conventions, and indexed state, with features like full-text search, task management, and a web dashboard.

Enables Claude Desktop to securely search and retrieve knowledge from an Obsidian vault through a stateless MCP interface, with progressive disclosure and gated write capabilities.

Lets any MCP-capable agent look up and extend a shared local store of entities, relations and facts about the user — people, projects, places, channels — resolving free phrases to cards and searching past conversations by words and by meaning.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

MCP server for Obsidian that exposes tools for reading/writing notes, managing frontmatter and tags, querying Tasks, semantic search, and interacting with Obsidian Bases, with shared local caching and support for various runtime modes.

Connects AI assistants to Obsidian vaults via the Local REST API to search notes, retrieve content, and perform semantic searches. It features self-healing multi-URL connectivity and supports both stdio and HTTP transports for flexible deployment.

Enables AI agents to store and retrieve durable memory as markdown notes in an Obsidian vault, with full-text and semantic search, wikilink graph operations, and human-auditable, editable storage.