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PopNx MCPAIを使う人のためのMCPサーバー · やさしい言葉で解説

Obsidian MCP Server

作者:maxkuminovバージョン 1.1.0i★ –iパソコンで動く
レジストリ名io.github.maxkuminov/obsidian-mcp

インストール

概要

作者による説明(英語の原文)

Self-hosted agent memory as a markdown vault: semantic and keyword search, wikilink graph, OAuth

PopNx MCPの3つの柱

この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。

できること

このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。

  • 接続方法: パソコンで動く
  • トランスポート: Streamable HTTP
  • カテゴリ: 検索・AIの記憶
  • 入力が必要なもの:DATABASE_URL, VAULT_PATH, SECRET_KEY, MCP_HOSTNAME, OPENAI_API_KEY

インストール

使っているAIアプリを選んで、設定をコピーしてください。

インストールの前に

  • 基本チェック:1項目中1項目に合格
  • あなたのパソコンで、あなたのユーザーと同じ権限(ファイル、ネットワーク、アプリ)で動きます。
  • 自分で入力するもの: DATABASE_URL, VAULT_PATH, SECRET_KEY, MCP_HOSTNAME, EMBEDDING_PROVIDER, OLLAMA_URL, OPENAI_API_KEY

「秘密」と表示された値は、あなたのアカウントの鍵です。絶対に人に教えたり、チャットに貼り付けたりしないでください。

必要なもの

  • DockerDockerのインストール

どのアプリを使っていますか?

上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。

Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます

{
  "mcpServers": {
    "obsidian": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DATABASE_URL",
        "-e",
        "VAULT_PATH",
        "-e",
        "SECRET_KEY",
        "-e",
        "MCP_HOSTNAME",
        "-e",
        "EMBEDDING_PROVIDER",
        "-e",
        "OLLAMA_URL",
        "-e",
        "OPENAI_API_KEY",
        "ghcr.io/maxkuminov/obsidian-mcp:v1.1.0"
      ],
      "env": {
        "DATABASE_URL": "your-value",
        "VAULT_PATH": "your-value",
        "SECRET_KEY": "your-value",
        "MCP_HOSTNAME": "your-value",
        "EMBEDDING_PROVIDER": "your-value",
        "OLLAMA_URL": "your-value",
        "OPENAI_API_KEY": "your-value"
      }
    }
  }
}

ターミナルでこれを実行します

claude mcp add obsidian --env DATABASE_URL=your-value --env VAULT_PATH=your-value --env SECRET_KEY=your-value --env MCP_HOSTNAME=your-value --env EMBEDDING_PROVIDER=your-value --env OLLAMA_URL=your-value --env OPENAI_API_KEY=your-value -- docker run -i --rm -e DATABASE_URL -e VAULT_PATH -e SECRET_KEY -e MCP_HOSTNAME -e EMBEDDING_PROVIDER -e OLLAMA_URL -e OPENAI_API_KEY ghcr.io/maxkuminov/obsidian-mcp:v1.1.0

動かす前に、空欄の値を入力してください。

Cursorで開く

または、設定を自分でコピーする

プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます

{
  "mcpServers": {
    "obsidian": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DATABASE_URL",
        "-e",
        "VAULT_PATH",
        "-e",
        "SECRET_KEY",
        "-e",
        "MCP_HOSTNAME",
        "-e",
        "EMBEDDING_PROVIDER",
        "-e",
        "OLLAMA_URL",
        "-e",
        "OPENAI_API_KEY",
        "ghcr.io/maxkuminov/obsidian-mcp:v1.1.0"
      ],
      "env": {
        "DATABASE_URL": "your-value",
        "VAULT_PATH": "your-value",
        "SECRET_KEY": "your-value",
        "MCP_HOSTNAME": "your-value",
        "EMBEDDING_PROVIDER": "your-value",
        "OLLAMA_URL": "your-value",
        "OPENAI_API_KEY": "your-value"
      }
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

VS Codeで開く

または、設定を自分でコピーする

プロジェクトの .vscode/mcp.json に貼り付けます

{
  "servers": {
    "obsidian": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "DATABASE_URL",
        "-e",
        "VAULT_PATH",
        "-e",
        "SECRET_KEY",
        "-e",
        "MCP_HOSTNAME",
        "-e",
        "EMBEDDING_PROVIDER",
        "-e",
        "OLLAMA_URL",
        "-e",
        "OPENAI_API_KEY",
        "ghcr.io/maxkuminov/obsidian-mcp:v1.1.0"
      ],
      "env": {
        "DATABASE_URL": "your-value",
        "VAULT_PATH": "your-value",
        "SECRET_KEY": "your-value",
        "MCP_HOSTNAME": "your-value",
        "EMBEDDING_PROVIDER": "your-value",
        "OLLAMA_URL": "your-value",
        "OPENAI_API_KEY": "your-value"
      }
    }
  }
}

ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。

これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。

選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。

自分で入力する値

  • DATABASE_URL 秘密 必須 env
    PostgreSQL 16 + pgvector (0.8.0+) connection URL for the app's NON-superuser role, e.g. postgresql+asyncpg://obsidian_mcp: @postgres:5432/obsidian_mcp. A superuser role or a CHANGE_ME password is ref…
  • VAULT_PATH 必須 env
    Path of the Obsidian vault inside the container (mount your vault read-write there).
  • SECRET_KEY 秘密 必須 env
    itsdangerous signer for cookies/sessions. Generate with `openssl rand -hex 32`; the app refuses to start on a placeholder.
  • MCP_HOSTNAME 必須 env
    Public hostname your reverse proxy routes to. Also derives BASE_URL, ALLOWED_ORIGINS and ALLOWED_HOSTS as https:// unless those are set explicitly.
  • EMBEDDING_PROVIDER env
    Embedding provider: `ollama` (self-hosted, default) or `openai` (bring your own key). Switching after deploy requires `make reset-embeddings`.
  • OLLAMA_URL env
    Ollama endpoint serving bge-m3 (used when EMBEDDING_PROVIDER=ollama). Must be https or loopback unless EMBEDDING_ALLOW_PLAINTEXT is set.
  • OPENAI_API_KEY 秘密 env
    OpenAI (or OpenAI-compatible) API key for text-embedding-3-* (required when EMBEDDING_PROVIDER=openai; the server refuses to start without it).

この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。

できること

パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。

基本チェックi

誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック

  • ✓ 合格

    作者とリポジトリが一致

    レジストリ名は、リポジトリを所有するGitHubアカウント maxkuminov で確認済みです

  • … 未チェック

    今もメンテナンスされている

    このリポジトリはまだGitHubから読み取っていません

  • … 未チェック

    ライセンスがある

    このリポジトリはまだGitHubから読み取っていません

  • – 対象外

    エンドポイントが応答する

    これはパソコンで動くため、インターネット上のエンドポイントはありません

  • – 対象外

    OAuthでサインイン

    パソコンで動き、代わりにローカルの設定を使います

  • … 未チェック

    ツールの説明に隠れた指示がない

    パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです

検索・AIの記憶のほかのサーバーとの比較i

  • このカテゴリのほかの7275件のうち0%よりスターが多い
  • このカテゴリのほかの7275件のうち95%より最近レジストリに公開
  • 基本チェックの結果が、このカテゴリのほかの7275件のうち100%と同じかそれ以上

レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。

よくある質問

Obsidian MCP Serverは安全ですか?

当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。

どんなキーやコードが必要ですか?

入力が必要なもの:DATABASE_URL, VAULT_PATH, SECRET_KEY, MCP_HOSTNAME, OPENAI_API_KEY

パソコンで動きますか、それともクラウドですか?

あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。

今もメンテナンスされていますか?

GitHubリポジトリの最終更新は–、最新バージョン(1.1.0)がレジストリに届いたのは一昨日です。

どのアプリで使えますか?

Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにDockerも必要です。

代わりに使えるものは?

同じカテゴリには:Context7, Codebase Memory, Exa

代わりの候補

同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。

カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i

Context7

作者:upstash

Up-to-date docs for AI agents

パソコンでもクラウドでも★ 64,224MIT昨日更新
インストール

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

パソコンで動く★ 48,148MIT21 日前更新
インストール

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

クラウドで動く★ 5,213MIT先月更新
インストール

作者のREADME

READMEを開く

作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。

Obsidian MCP Server

Your agents' memory, in the vault you already have, reachable from claude.ai, ChatGPT, Claude Code and your phone.

A self-hosted Model Context Protocol server over an Obsidian vault. Three things it does that the alternatives mostly don't:

  • Your existing vault, served in place. No imposed note format, no sidecar syntax, no "memory" folder you have to adopt. Agents read what you read, follow your wikilinks, and pick up your folder layout, frontmatter schema and tag conventions from the vault itself.
  • Remote and multi-user. OAuth 2.0 PKCE and API keys, so claude.ai, Claude Desktop, Claude mobile, ChatGPT, Claude Code and n8n all read and write the same files, each user confined to their own vault root.
  • Writes cannot clobber. expected_hash preconditions refuse an edit made from a stale read, every publish is atomic and no-clobber by default, deletes go to .trash/, and dry_run returns the diff before anything lands.

Connect from Claude Code:

claude mcp add obsidian --transport http \

--url "https://obsidian-mcp. /mcp" \ --header "Authorization: Bearer omcp_..."

In claude.ai, Claude Desktop or ChatGPT, add a custom connector at https://obsidian-mcp. /mcp and sign in through the OAuth consent page. Connect a client has the rest.

Stack: Python 3.12, FastAPI, PostgreSQL with pgvector. Pluggable embeddings (Ollama — bge-m3 by default, qwen3-embedding:0.6b in the reference deployment — or OpenAI text-embedding-3-{small,large}).

Contents

  • Why this exists
  • A session at the keyboard
  • A session away from the keyboard
  • What's in the box
  • vs. other Obsidian MCP servers
  • vs. hosted memory systems
  • vs. an agent with raw file access
  • Who this is for
  • Control panel
  • Quick start
  • Versioning and compatibility
  • Upgrading
  • Cost expectations
  • The self-describing vault
  • Multi-user mode
  • Configuration
  • Architecture
  • Project layout
  • Development
  • Security notes

Why this exists

There are three things going on here, and they're more interesting together than apart.

1. Agent memory that you can actually read

If you let an agent run for a while, it needs memory. Most setups solve this with an opaque vector store, a SQLite blob, or a managed "memory" service that you can't see into. That works until you want to know what the agent thinks it knows about you, or you need to correct something, or you want to understand why it just made a weird suggestion.

This server gives you a different deal. Agent memory lives as markdown files in your vault. Folder structure, file names, frontmatter, all visible. You can open the file in Obsidian and read it. You can edit it. You can delete it. You can grep it. The agent's "memory" is a human-auditable artifact that sits in the same place as your own notes, with the same tools available.

The home lab is the use case that sold me on this. My vault has notes on the rack, the network, and every Home Assistant integration. I can say "set up a night-light mode in the master bathroom, 1% after 11pm" and a sysadmin agent finds the right config, makes the change, and updates the doc in the same pass. Six months later when I've forgotten how it works, the answer is in the vault, not buried in some chat history I can't search.

The semantic search and wikilink graph still work over that material, so retrieval is fast and conceptual. But the substrate is files you own, not a black box.

To be precise about the scope: what the server supplies is MCP-accessible storage, keyword and semantic search, and graph operations over markdown notes, for whatever MCP clients you connect. The agents direct their own reads and writes. There is no extraction or decay pipeline running behind them, and nothing rewrites a note because a model judged it stale: an agent remembers something because it wrote a note, and forgets it because someone deleted one. By late 2026 that is less of a contrarian position than it sounds. Every vendor's consolidation step (the "dreaming" or "sleep-time" job) has turned into a separate process you can inspect, rather than silent extraction inside the write path. This server keeps the agent as the author. The consolidation help it will grow is a hygiene report that proposes merges and flags duplicates, and never writes (#359), not a pipeline that edits your notes while you are not looking.

2. A shared memory layer between you and your agents

The other half runs the other way: the vault isn't only the agents' memory, it's mine. I think of my Obsidian vault as my exocortex. The "big me" that includes notes, calendars, scripts, search, and AI assistants is substantially more capable than the "small me" of the biological brain alone. It's also where I do most of my thinking, because writing something down is itself a form of thought.

The problem is that until recently, the vault was passive. I had to go find things. Agents that wanted to help me had to be briefed from scratch every session, and they had no way to see what I'd already written about a topic.

This server fixes that. Now the same vault feeds my own daily writing and any agent I plug into it. The agent reads what I read, links what I link, follows the same wikilinks, sees the same frontmatter. When I write a project note on Sunday, my Monday-morning briefing agent already knows about it. When the agent leaves notes from a research session, they show up in my normal Obsidian search.

A concrete version of this: I'll spend a session in Claude Code on a project, wrap up, push the commits, and then just say "update Obsidian." The agent reads the vault guide, figures out where project notes live in my structure, picks the right format and frontmatter, and leaves a session log I can later roll into a status report. No path-passing, no telling it what to write — the conventions are already in the vault, and it follows them.

That's the exocortex idea made concrete: one place that holds context, and both the human and the agents reading and writing into it on the same terms.

3. The vault follows you

The thing that still surprises me is that this is internet-facing. Same vault, same notes, reachable from anywhere I happen to be talking to an agent — Claude in a browser tab, Claude on my phone on the train, an n8n workflow firing on a schedule, a Claude Code session on whatever laptop is in front of me. All behind OAuth or a bearer key, all hitting the same source of truth.

So when I hear an interesting podcast on a commute and want to think out loud about it with Claude on my phone, the agent isn't starting cold. It can pull up what I've already written on adjacent topics, surface a note I half-finished six months ago, and at the end of the conversation suggest updates and write them in. The vault doesn't have to be near me to be the thing I'm working in. (A session away from the keyboard walks through exactly one of these.)

A session at the keyboard

To make the abstract concrete, a short transcript from a real session. Tool calls inline; the user types in plain English and the agent picks the right tool.

you  > find anything I've written about why retrieval-augmented

chat is hard

claude → semantic_search(query="why retrieval-augmented chat is hard") • 2025-12-03 - RAG failure modes.md • 2025-10-18 - Chunking tradeoffs.md • 2024-06-22 - Vector recall vs precision.md

the closest hit is your December note on RAG failure modes. let me see what it's connected to.

→ get_neighborhood(path="2025-12-03 - RAG failure modes.md", depth=1) 8 connected notes. notable ones: • "Hybrid search" — a re-ranking design you sketched but didn't ship • "Out-of-distribution queries" — a half-finished draft from October • "Embedding model choice" — links to bge-m3, your current model

you have three connected pieces here: a failure-modes catalog, an unshipped hybrid-search sketch, and an abandoned O-O-D draft. want me to summarize all three together, or pull up the draft so you can decide whether to finish it?

you > pull up the draft, and tag it #revisit-2026 in frontmatter while you're there

claude → read_note(path="2025-10-18 - OOD queries (draft).md") → set_frontmatter( path="2025-10-18 - OOD queries (draft).md", updates={"tags": ["draft", "rag", "revisit-2026"]} )

here's the draft, and the tag is on. you stopped right before the section on confidence thresholds; the open question you left yourself was…

Two things to notice. First, the agent didn't need to be told what folder to look in or what tools to use — it picked them. Second, the write at the end is structured (set_frontmatter mutating YAML, not a regex over the file body), so the note round-trips cleanly. The self-describing vault and the wikilink graph are doing the work that makes this feel natural.

A session away from the keyboard

The transcript above is the easy case: I'm at a desk, I can see what the agent is doing, and Obsidian is one alt-tab away. The session that actually changed how I think about this server had none of that.

I was out walking with a health podcast in my ears — a long one, two people who clearly disagreed with each other, an hour of it. I had my phone and no intention of going home to a laptop. So I pulled the episode's transcript, handed it to Claude on my phone, and we talked it through while I kept walking: what the actual claim was, which parts I already had notes on, where it cut against something I'd decided months ago and written down at the time.

The agent had the vault the whole way. It surfaced what I'd already written on the topic, flagged that two dates in an older note were wrong, and asked whether a decision I'd recorded last year still stood given what the episode argued. By the time I got back it had written all of it in: the health-related decisions I'd actually landed on during the walk, the date corrections in the old note, a couple of new notes on the episode itself — and, because the conversation kept circling back to it, a durable note on how I decide which experts to trust on medical questions in the first place. That last one is the artifact I keep returning to. It wasn't about the episode at all; it was the reasoning underneath a whole class of decisions, and it now sits in the vault where the next agent will find it.

I never opened Obsidian. Not on the walk, not when I got home. The whole session — retrieval, argument, correction, and the writing that came out of it — went through an agent, and the vault is simply where it landed. Obsidian is how I check the w

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