"Information about playwrights or Playwright (context-dependent)" matching MCP servers:

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

Enables LLMs to access a user's personal writing context—voice, style, opinions, expertise, projects, and communication patterns—via curated markdown files, helping the LLM match the user's voice when generating written content.

Stores personal context as markdown files and exposes them via MCP for AI assistants to retrieve user preferences, skills, and background.

Enables MCP clients to query project-scoped Graphify graphs, search, read, and write Obsidian Markdown notes, and recall or store persistent ICM memories over authenticated private HTTPS. It serializes access per project and supports slim and standard Docker deployments without embeddings or extra memory services.

The server provides tools for web automation using Playwright, allowing navigation, interaction, and JavaScript execution on web pages, and supports note storage with summarization capabilities.

Parses an Obsidian vault and exposes structured context (notes, blocks, tasks, headings) through MCP tools, enabling AI clients to query and reason over local markdown notes.

An open-source memory layer that provides persistent project context and architectural history for AI development tools across multiple platforms and sessions. It enables AI assistants to maintain a shared understanding of codebases while integrating directly with services like Notion for documentation management.

An MCP server for saving, managing, and enhancing context with pre-processing strategies like clarification, analysis, and search optimization.

Enables MCP-compatible clients to query an Obsidian vault through a local, read-only broker, returning compact, cited context packs with source paths and heading anchors while enforcing a fail-closed sensitivity boundary.

A simple notes MCP server that enables creating, listing, and summarizing text notes via resources, tools, and prompts.

Lets AI agents retrieve source-linked passages from a local folder of Markdown notes or an Obsidian vault, optionally following the explicit links between notes, and can also fetch passages from pinned public GitHub files you configure. It returns bounded evidence packets with original text, file paths and hashes so agents can answer from your material rather than generating content themselves.

Enables AI clients to locally store and share tasks, work activities, long-term memory, knowledge, and people information, while allowing users to review saved content and generate briefings or reports through a web UI.

Enables Claude to pull curated context from self-hosted Markdown files via a remote MCP connector, with an append-only journal for agent notes manually promoted by the owner.

Self-hosted, single-owner MCP relay that lets an agent client queue requests for an authorized ChatGPT worker to look up context from permitted sources, apply bounded edits to a specific Page, or save a selected transcript as a new Page. Requests, results, and status are stored in the owner's own Cloudflare account, with the worker woken by signed events and results retrieved by polling.

Enables ChatGPT to search, read, and organize your Google Keep notes through read-only MCP tools, including full note retrieval, label listing, recent-note browsing, and task extraction. Notes refresh automatically from your connected account without any local database or write access.

Enables a local-first Codex plugin to maintain durable OKF memory, manage scoped project and personal context, and perform reviewed selective encrypted exports and recovery.

Enables multiple users to share an AI-maintained markdown knowledge base with per-person privacy enforced by the server, so any MCP-capable assistant can recall and save private notes, tasks, and decisions alongside reviewed team and role-gated silos. Access is scoped by identity-provider roles, keeping each person's silo readable only by them while shared knowledge stays available to the whole team.

Enables agents to import selected conversation archives, search and edit an Obsidian-compatible Markdown memory wiki, and read/write shared context across AI clients through MCP.

Persistent memory for AI agents enabling saving, searching, and managing knowledge across sessions with local markdown files.

This MCP server provides an AI-powered productivity suite that connects Todo, Idea, Journal, and Timer apps with AI

Give your AI persistent, structured memory and let humans see it too. It stores project knowledge as Markdown files in a hierarchical tree, accessible via MCP tools and a built-in Web UI.

Private tooling to stage ChatGPT conversations into reviewable Homebase markdown and Notion drafts with redaction and classification.

Enables managing personal information with dynamic topic-based organization (tasks, meetings, contacts, etc.), supporting optional OTP authentication and AES-256 encryption for sensitive data with automatic backups.

Enables AI agents to maintain a structured Markdown or Obsidian memory vault with tools for reading, writing, searching, and organizing notes.

Provides AI clients with per-project todo management and persistent context notes via MCP, enabling task tracking and resume summaries.

An MCP server for managing contextual data as markdown files with metadata, enabling agents to save, retrieve, search, and delete contexts using simple CRUD operations.

A stateless MCP server providing persistent, structured project memory for AI coding agents via a markdown folder. It allows agents to record decisions, plans, and notes, which are stored and synced with git.

Enables AI agents to read, search, and preview governed markdown memories with explicit state and sensitivity, plus quarantine-only write, while never mutating canonical memory or exposing undeclared content.

Enables AI agents to read, search, create, and append Markdown notes from a local vault (e.g., Obsidian) via MCP, allowing natural-language note management through compatible clients.

Enables deterministic, token-minimal multi-hop retrieval from a vault of [[wikilink]] notes via the Model Context Protocol, allowing LLMs to answer questions by following authored links without vector databases or LLM calls during retrieval.