"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 semantic search and reading of Obsidian Markdown notes through read-only MCP tools, allowing Claude to retrieve relevant passages from a local vault.

MCP server to interact with Obsidian via the Local REST API community plugin.

A standalone Node MCP server that provides semantic search, knowledge graph, and vault editing over an Obsidian vault. It runs locally as a single stdio process without requiring an Obsidian plugin for core functionality.

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

Wraps the official Obsidian CLI to expose vault tools for MCP clients, enabling note management, search, tasks, properties, and more through Obsidian's internal API.

This MCP server turns any Obsidian vault into an AI-queryable knowledge graph, enabling graph traversal, search, and backlink-aware note manipulation without requiring Obsidian to be running.

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

Enables semantic search and note management for Obsidian vaults via the Model Context Protocol, allowing LLMs to search, read, and index notes, PDFs, and web pages locally.

MCP server for reading and searching Markdown notes in any directory, such as an Obsidian vault. It integrates with MCP clients like Claude Desktop to access note contents.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

Lets coding agents search the official Obsidian directory of 8,900+ community plugins and 870+ themes, with download counts, latest versions and last-update dates, so they can check what already exists or spot gaps before writing code. It also works for picking a plugin or theme to install, needs no API key, and only reads public data.

Local-first persistent memory MCP: shared SQLite key/value store, searchable, TTL-aware and secret-safe.

MCP server for persistent, semantic memory across AI sessions; store context, decisions, and learnings and recall them with natural language search.

Read-only semantic retrieval for agents that need to find the right Obsidian note without write access.

Provides AI agents with persistent, long-term memory via OKF-formatted markdown and SQLite indexing, enabling stateful storage, retrieval, and search across sessions.

MCP server for persistent, cross-session, local-first memory for AI agents, storing memories as Markdown files with SQLite indexing for hybrid search.

A local-first MCP server for durable agent memory using SQLite and FTS5, enabling knowledge graph storage, search, and recall for AI agents.

A persistent memory layer for Claude Desktop that enables semantic search across your entire Obsidian vault using local embeddings and PostgreSQL + pgvector.