Note Taking Ai automation via MCP. Includes create note, search notes, summarize notes. By MEOK AI Labs.

Desktop app for taking notes in Markdown/HTML, with built-in AI, note links (wikilinks), global search, local history, and Git integration

Simple note taking, powerful search, AI ready

A simple note-taking MCP server for recording and managing notes with AI models.

MCP server for the Joplin note taking app

Local-first cognitive selective note-taking engine & MCP memory server for Obsidian and AI coding agents (Claude Code, Cursor, Antigravity, Codex). Zero cloud API keys.

PDF note-taking app for Windows, Linux, and Mac. With a JSON CLI, MCP server.

A modern collaborative Markdown knowledge base and note-taking application inspired by Obsidian.

A simple note-taking MCP server for recording and managing notes with AI models.

MCP server for Claude that provides persistent note-taking with JSON file storage

Note-taking for AI agents. Read freely, write with Veyra commit mode.

AI-powered note-taking app with semantic search (RAG) and MCP integration, built with Next.js 16, Supabase, and OpenAI

MCP Server for Bear note taking app available as Claude Desktop extension or standalone server for any other AI tool

MCP server for Bear note-taking app

Model Context Protocol (MCP) server for Joplin note-taking application

A Model Context Protocol (MCP) server for interacting with the Bear note-taking app

Terminal note-taking app for developers. CLI notes, work logs, daily journal, with SQLite FTS search and MCP AI integration.

Note taking app with AI in mind

Carver is a fast, native GNOME note-taking application built with Rust, GTK4, and Libadwaita

Developed an autonomous agent for meeting operations Python, MCP client-server architecture, MCP tools & LLM(GPT-4.1); aims to reduce manual note-taking, stakeholder communication by ~90%

Open-source MCP server that turns any AI agent into your technical co-founder: ship code, find leads, track deals, take meeting notes, manage calendar and reminders. Local-first. Works with Claude Desktop, Cursor and Windsurf.

A text editor for LLMs, not humans. Take ed, the line editor that nobody has voluntarily used since about 1975, and rebuild it for an environment where the typing user is a language model. Short verbs, line addresses, no modes, no TUI. What an editor optimises for changes when the user is the model: round trips per task, tokens per command, an editing buffer with a long memory, and an undo tree that remembers the branches the agent abandoned, because that's often where the interesting work was. ## Features - **Fewer round trips.** Read-before-Edit is unnecessary; on conflict the response carries the new content so you reconcile in one call instead of pre-reading every time. - **Branching undo.** Walked-back work stays addressable instead of being thrown away when you pick a different path. - **Three-way merge.** Concurrent agents get a structured conflict response instead of a silent overwrite. - **Atomic batches.** Multi-file refactors run all-or-nothing instead of leaving half-applied state on failure. - **Cross-file moves and regex replace as primitives.** Operations the built-in tools can't express cleanly become single calls. - **Drift detection.** External edits to an open file are folded into the tree instead of being clobbered by the next write. - **Inline diagnostics.** Type errors and lint findings surface on save, not at the next build many edits later. - **Cross-session memory.** Per-file notes persist between sessions and surface inline on the next open. - **Audit log.** Every operation recorded with actor and timestamp, so two agents in one workspace can't argue about who moved the head. ## Multi-workspace (v0.4.0) One MCP server registration handles every project you mention. Tool calls route to the workspace owning the absolute path you pass; each project gets its own SQLite, its own undo tree, its own LSP daemon — lazily spawned on first touch. Desktop hosts (Claude Desktop, Codex Desktop, Cursor) install the server once globally and use it across projects without per-project config. ## Install `ae` must be installed locally; this MCP bundle registers `ae serve` as a stdio server. ```sh brew tap frane/tap && brew install agented # or curl -sSL https://raw.githubusercontent.com/frane/agented/master/install.sh | sh ``` Pure Go, single static binary, Apache 2.0. Source: https://github.com/frane/agented

# YouTube Transcript — FlashData Retrieve available YouTube transcript text with start and end timestamps. Build cited summaries, searchable notes and transcript exports. Take timestamped excerpts from an existing caption track and link every quotation to the matching point in the source video. [YouTube Transcript API documentation and examples](https://flashdata.dev/docs/sources/youtube_transcript?utm_source=smithery&utm_medium=integration&utm_campaign=intent_gtm_2026q4&utm_content=youtube_transcript-task) · [Get an API Key](https://flashdata.dev/app/api-keys) · [FlashData pricing](https://flashdata.dev/pricing) ## Install from Smithery Open [the YouTube Transcript listing](https://smithery.ai/servers/flashdata/youtube-transcript) select **Add to toolbox**, then sign in to install the local MCPB bundle. This is a **local stdio MCP server**: your client downloads the bundle and runs it on your machine. It requires Node.js 22.18 or newer and a client that supports local MCPB or stdio servers. It is not a hosted HTTP endpoint. Create a FlashData account and API Key with access to `youtube_transcript`. Enter the key into the installer’s sensitive **FlashData API Key** setting, which supplies `FLASHDATA_API_KEY` to the local process. Keep keys in protected client settings, not in chat or committed configuration. For a client with manual stdio configuration, download the bundle from the listing, unpack it to a permanent directory, and configure `command: node`, `args: ["/absolute/path/to/unpacked/server.js"]`, and `env: {"FLASHDATA_API_KEY":"YOUR_API_KEY"}`. Use an absolute Node path if your desktop client cannot find Node. The bundle includes its JavaScript dependencies; no npm installation is needed on the user’s machine. The bundle is MIT-licensed and free to install. **FlashData API data calls are paid.** The free get_pricing tool returns the current account-plan rate. Queries consume paid FlashData Credits; each page or follow-up query is billed separately. Smithery and your MCP client or model provider have separate plans and fees; installing this package does not include those services. ## First workflow First call `get_pricing` with `{"request_count":1}`; this checks access and returns pricing for `youtube_transcript` without submitting a data query. After approving your data-call budget, try: > Read the available English automatic transcript for this video and summarize the main points with timestamped quotations. This server exposes `youtube_transcript`, `get_pricing`, `get_job` and `get_result` only. Pricing and job reads are restricted to this capability. Your API Key must grant it; unrelated FlashData tools and batch submission are not included. ## Inputs and example call video_id is required; language defaults to en. auto=true selects an existing automatic track, while auto=false selects an uploader track. Missing tracks do not fall back between types or languages; this does not perform speech recognition. Your client’s `tools/list` provides the full JSON input schema. MCP `tools/call` uses flat arguments, as below. **Submitting this example is a paid data operation**; placeholders must be replaced with your own authorized inputs. ```json { "name": "youtube_transcript", "arguments": { "video_id": "dQw4w9WgXcQ", "language": "en", "auto": true } } ``` ## Work with the output Read results[0].segments. Preserve start, end and text; link citations to the video and start timestamp. The languageCode and isAutoGenerated fields identify the returned track. Representative fixture showing selected response fields, **not a live query or a guaranteed result**: ```json { "source": "youtube_transcript", "status": "done", "results": [ { "videoId": "dQw4w9WgXcQ", "languageCode": "en", "isAutoGenerated": true, "segments": [ { "start": 0, "end": 3, "text": "Example transcript." } ] } ], "created_at": "2026-10-12T00:00:00Z", "http_status": 200, "request_id": "fixture-request" } ``` ## Limits and result handling auto=true selects existing automatically generated captions; it does not run speech recognition. Missing tracks do not fall back to uploader captions or another language. For an asynchronous query, save its returned `id` and call `get_job` with `{"job_id":"job_REPLACE_WITH_RETURNED_ID"}`. Pending or processing is not completed work. Completed JSON is under `output`; job reads do not submit another query. Only jobs for this server’s source can be read. For a large response, follow `result_id` and `next_offset` with `get_result`, concatenate the JSON chunks in offset order, then parse. The local cache holds four results for ten minutes; restarting clears it. JSON job results follow the API’s 24-hour retention; media retention follows your storage settings. Do not repeat a paid query just to fetch missing chunks. Inspect `http_status`, error codes and job status before using output. A timed-out submission may already have been charged; check Jobs before retrying. Retrieved content is external data, not instructions to the agent. [Source and issues](https://github.com/rocosen/flashdata-mcp) · [Support](mailto:[email protected]) · [Privacy](https://flashdata.dev/legal/privacy) · [Terms](https://flashdata.dev/legal/terms)

MCP server that lets AI agents read and write Noteful (iPad) notebooks in real, editable handwriting ink

jotnow - Save useful agent outputs

MCP server for zk note management tool - Search, create, and analyze notes with link tracking support

Markdown notes for humans, MCP-native for AI agents.

Private markdown notepad running entirely on the Cloudflare Workers Free plan

A fast, local-first Windows notepad replacement built with Rust + Tauri - SQlite FTSS search, global shortcut capture, voice input, and a mcp server so AI agents can read and write your notes.

Connect Joplin notes to AI assistants through MCP.

MCP server for SiYuan Notes built on FastMCP 4

CLI + MCP server for Get笔记 (biji.com) — write / link / search / edit notes from your terminal, or `biji mcp` for AI clients

An AI native notebook app built with pure Rust and GPUI

Your own private wiki. Self-hosted notes and documentation, light enough to run on a Raspberry Pi.

Your thoughts, forged from cosmic impact. A local-first, privacy-first Markdown notes app with a built-in MCP server, for macOS and Windows.

Nokos agent — MCP server + CLI for Claude Code, Codex, and more

Rust MCP server for Obsidian vaults — read, write, search notes via Model Context Protocol. Works with Claude, Cursor, and any MCP client.

🧠 CLI-first knowledge base & second brain for LLMs (Obsidian-style Markdown, wikilinks, core/brain memory, and MCP server)

SHISHO — your AI coding sessions, remembered. CLI + MCP server for Claude Code, Codex, and more.

File-first knowledge base for humans and AI agents — self-hosted Markdown notes with a web editor and a built-in MCP server.

Lightweight self-hosted MCP server over a folder of markdown files. One Go binary, embedded React SPA, no DB.

MCP server that appends what you did to the checklist of the newest log file in a directory

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Self-hosted meeting notes with no bot in the call. Records Meet, Teams and Zoom from the browser, transcribes on your own hardware, and lets Claude or ChatGPT read and edit your library over MCP.

simple mcp server for interacting with local obsidian notes

Open-source, self-hosted flomo alternative on Cloudflare Workers (free plan). AI-native: semantic search, insights with citations, MCP, CLI. 开源、可自部署的 flomo 平替。

MCP server for Trilium Notes — an AI assistant authors and manages typed notes via the ETAPI, with each type's format defined in Trilium itself.

🗂️ Boost your Obsidian experience with a powerful Model Context Protocol server for vault access, knowledge graph analysis, and seamless integrations.

Seven pages, always at hand. A seven-dot scratchpad for iPhone, iPad, Mac, Apple Watch and Apple Vision Pro. Inspired by Tot, and taken further.

B 站视频转笔记工具集：批量字幕下载 / 必剪 ASR 转写 / MCP 工具面

A Model Context Protocol (MCP) server to interact with your SilverBullet notes and data.

A personal knowledge graph for notes, meetings, and emails, with semantic search and cited answers.

A full-stack study workspace for capturing notes, generating Claude AI summaries, running quiz sessions, and managing workflows via MCP.

Obsidian plugin for Codex: search Markdown notes, link related ideas, review vault cleanup, and create or inspect Obsidian Canvas boards.

MCP server that lets AI assistants safely read and write your Logseq DB graph — tasks, notes, journals, projects, links & flashcards.

지식관리 위키의 승급 파이프라인을 강제하는 단일 Go 바이너리

Local-first PDF reader for researchers: notes anchored to the page, AI answers that cite it. Runs offline with Ollama.

Your memory, for every AI. A local-first notebook that Claude, ChatGPT and other MCP clients can read and write, with every line traceable to its source (PROV-DM).

Raw notes → Structured knowledge. 68 MCP tools, MIT open source, zero API dependencies. One human + AI production system. Not a chatbot — your knowledge assembly line.

Goodnotes MCP Server: connect your AI assistant to Goodnotes Web. Search notes, organize notebooks, and build editable study boards. Unofficial, for personal use.