mcp-server-sample
mcp-server-sample — メモを保存・検索する最小の MCP サーバー
メモを保存・検索するだけの、最小の MCP サーバーです。外部システムへは一切繋ぎません。
保存先は同じフォルダの notes.json 1ファイルだけです。
MCP の3つのプリミティブを、1つずつ持たせてあります。
プリミティブ | 誰が決めるか | このサーバーでの中身 |
Tools | モデルが判断する |
|
Resources | AI アプリが取得して渡す |
|
Prompts | ユーザーが明示的に選ぶ |
|
必要なもの
Node.js 24 以上(LTS。
node --versionで確認)git
Related MCP server: mcp-snippetbox
セットアップ
git clone https://github.com/utakatano/mcp-server-sample.git
cd mcp-server-sample
npm installnpm install が通れば準備完了です。この時点では起動しません。
MCP サーバーは AI アプリが起動するので、自分でターミナルから走らせる必要はありません。
AI アプリに繋ぐ
Claude Code
claude mcp add notes -- node /絶対パス/mcp-server-sample/index.jsclaude mcp list で ✔ Connected と出れば繋がっています。
Claude Desktop
設定 → Developer → 「Edit Config」で claude_desktop_config.json を開き、次を追記します。
{
"mcpServers": {
"notes": {
"command": "node",
"args": ["/絶対パス/mcp-server-sample/index.js"]
}
}
}保存したら Claude Desktop を完全に終了して起動し直します(ウィンドウを閉じるだけでは反映されません)。
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
動作確認
「来週までにネットワーク構成を確認する」とメモして「ネットワーク」を含むメモを探してnotes.json が作られ、中身が増えていくのが確認できます。
保存先を変える
環境変数 NOTES_FILE に絶対パスを渡すと、保存先を変えられます。
{
"mcpServers": {
"notes": {
"command": "node",
"args": ["/絶対パス/mcp-server-sample/index.js"],
"env": { "NOTES_FILE": "/絶対パス/my-notes.json" }
}
}
}繋がらないとき
まずログを見ます。原因はたいていここに出ています。
tail -20 ~/Library/Logs/Claude/mcp-server-notes.log # macOS
# Windows: %APPDATA%\Claude\logs\mcp-server-notes.logServer started and connected successfully のあとにエラーが続いていないかを見てください。
ログに出ているもの | 原因 | 対処 |
|
| リポジトリ直下で |
| AI アプリから |
|
| 依存が入っていない | リポジトリ直下で |
ログが空、または更新されない | 設定が読み込まれていない | JSON の構文(カンマ・括弧)を確認し、Claude Desktop を完全に終了(macOS は ⌘Q)してから起動し直す |
サーバー側か AI アプリ側かの切り分けは、手元で直接叩くのが速いです。
printf '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{"_meta":{"io.modelcontextprotocol/protocolVersion":"2026-07-28"}}}\n' \
| node /絶対パス/mcp-server-sample/index.jsadd_note と search_notes を含む JSON が返ればサーバーは正常です。その場合は AI アプリ側の設定(パス・JSON の書き方・再起動)を疑ってください。
サプライチェーン対策
npm パッケージの乗っ取りを想定した設定を .npmrc に入れてあります。npm install / npm ci のたびに効きます。
設定 | 何をするか |
| インストール時に依存パッケージのライフサイクルスクリプト( |
|
|
| 公開から7日を過ぎたバージョンだけをインストールする。npm はこれを |
依存は package.json で完全固定(@modelcontextprotocol/server は 2.0.0、zod は 4.4.3)、
package-lock.json に integrity ハッシュ付きで記録してあります。
lock のとおりに入れたいときは npm install ではなく npm ci を使ってください。
依存を更新するときは、意図して1つずつ上げます。
npm outdated
npm install @modelcontextprotocol/server@2.1.0 # save-exact により完全固定で書かれる
npm ls --all # 増えた依存を目で確認するライセンス
MIT
Available Tools
2 toolsadd_noteメモを追加するA
メモを1件保存する。打ち合わせの決定事項や、あとで思い出したいことを記録するときに使う。
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | 分類用のタグ(任意) | |
| text | Yes | 保存する本文 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states '保存する' which implies mutation, but it does not disclose potential side effects, permissions, or behavior on duplicates. For a simple create operation, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the essential action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters, no output schema, and no annotations, the description is fairly complete. It explains the primary use case and differentiates from the sibling. It could mention the return value but is not required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both parameters described. The tool's description adds no new information about the parameters; it only restates the purpose. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb '保存する' (save) and resource 'メモ' (note), and it is distinct from the sibling tool 'search_notes' which is for retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit context for when to use: '打ち合わせの決定事項や、あとで思い出したいことを記録するときに使う' (use when recording meeting decisions or things you want to remember later). It does not explicitly exclude other scenarios, but the purpose is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_notesメモを検索するB
保存済みのメモをキーワードで検索する。本文とタグの両方を対象にする。
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | 検索キーワード |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It states search targets both body text and tags, but lacks details on whether searches are case-sensitive, support partial matches, or have rate limits. It does not mention return format or pagination. The description adds modest value but is insufficient for a tool lacking annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is concise and front-loaded with the action and target, then expands on scope. Every phrase adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is simple (1 parameter, no output schema, no nested objects), the description is minimally adequate. It covers the search target and scope. However, it omits any mention of results behavior (e.g., whether it returns full notes or summaries) and does not compensate for missing annotations, but the low complexity reduces the burden.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter 'keyword'. The description adds meaningful context by specifying that keyword searches both body and tags, which the schema description ('検索キーワード') does not convey. This enriches the semantic understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly specifies the action (検索する), the target (保存済みのメモ), and the search scope (本文とタグの両方). It distinguishes from add_note, which creates notes. However, it does not explicitly contrast the two, leaving a slight gap in sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for keyword search but gives no guidance on when to use this vs. add_note, nor does it mention any context or prerequisites for searching. No exclusion criteria or alternative scenarios are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
v1.0.0- First observed
add_note - First observed
search_notes
TDQS
Scored across 2 tools
The two tools have completely distinct purposes: one creates/ stores a note, the other retrieves notes via search. There is no overlap or ambiguity between writing and searching.
Both tool names follow a consistent verb_noun pattern (add_note, search_notes) using lowercase with underscores. The naming is predictable and clear.
With only 2 tools, the set feels minimal. While the tools cover basic create and read/search operations, the server's purpose (saving and retrieving notes) could reasonably include more tools (e.g., update, delete, list tags) to avoid being overly thin.
The domain is a personal note-taking system, but only add and search operations are provided. Missing critical operations like update, delete, and get all notes (without search) create significant gaps that would frustrate or block a typical agent workflow.
Maintenance
Related MCP Connectors
Google Keep-style notes app with an MCP server for AI agents to read/write notes.
- TaprootOAuthcom.taproothq
Persistent memory layer for AI tools. Save and recall notes across Claude and other MCP clients.
Search, read, and write your Apple Notes from ChatGPT/Claude via a local Mac agent + MCP relay.
MCP-native notes and memory for ChatGPT, Claude, and other AI tools.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceEnables adding, getting, and listing notes through MCP, with state persisted to a JSON file in the home directory.MIT
- AlicenseNot gradedqualityCmaintenanceEnables managing notes through a simple MCP server, providing tools to add, retrieve, update, delete, and list notes for use with Claude Desktop.MIT
- FlicenseNot gradedqualityCmaintenanceEnables AI clients to create, list, and search notes stored in a local JSON file through the Model Context Protocol.-
- AlicenseNot gradedqualityCmaintenanceEnables Claude Desktop to add, retrieve, update, delete, and list notes persisted in a JSON file whose path is set via MCP_NOTES_FILE or --notes-file, with atomic, lock-protected saves.MIT