Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Persistent understanding via workflow prompts, typed updates, graph-native code, and supersession.
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。
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。
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。
必要なもの
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": {
"understanding-graph": {
"command": "npx",
"args": [
"-y",
"understanding-graph",
"mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add understanding-graph -- npx -y understanding-graph mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"understanding-graph": {
"command": "npx",
"args": [
"-y",
"understanding-graph",
"mcp"
]
}
}
}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。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"understanding-graph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"understanding-graph",
"mcp"
]
}
}
}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。
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。
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。
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
レジストリ名は、リポジトリを所有するGitHubアカウント emergent-wisdom で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
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
パソコンで動き、代わりにローカルの設定を使います
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
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。
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。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
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)。
GitHubリポジトリの最終更新は–、最新バージョン(0.2.1)がレジストリに届いたのは8 日前です。
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Node.jsも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, Tools MCP
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
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Web production tools for AI agents: contrast, JP text, WebP, JSON-LD, slugs, dates and 40+ more
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。
A persistent medium for recursive, inspectable understanding.
Understanding Graph is an MCP server that gives AI agents structured, persistent memory. Unlike knowledge bases that store facts, it stores externally useful *understanding updates* -- tensions, surprises, decisions, evidence, and how beliefs evolved over time. It does not require private chain-of-thought. Multiple agents can coordinate through the graph itself: each agent reads what others have written, builds on it, and leaves inspectable traces for the next -- stigmergy.
| Traditional Memory | Understanding Graph |
|---|---|
| Stores facts | Stores authored understanding updates |
| "User prefers dark mode" | "User switched to dark mode after eye strain -- tension between aesthetics and comfort resolved toward comfort" |
| Flat retrieval | Typed, revisable interpretation |
| Loses the interpretive middle | Preserves recorded rationale and revision |
| Single agent | Multi-agent coordination through shared graph |
Core insight: AI agents don't just need to remember facts -- they need the usable before state, pivoting evidence, updated conclusion, and remaining uncertainty. That lets later work test or revise a conclusion without reconstructing hidden deliberation.
Requires Node.js 22 or newer.
Run the initializer in the directory where you want the graph-backed work to live:
cd your-project
npx -y understanding-graph@0.2.1 init
It creates project-scoped MCP configuration for both Codex and Claude Code, installs the same fluid-understanding contract in AGENTS.md and CLAUDE.md, installs a project-scoped reading-mode skill for both clients, and adds the local projects/ path to ignore rules without installing any starter graph. Open either client, sign in with your normal ChatGPT or Claude subscription, and ask for the actual research, writing, coding, or decision task. The agent creates a descriptively named graph when real work begins. You do not need to say “use the graph.” The model runs in the subscription client; Understanding Graph itself makes no model API calls.
For a fresh chronological reading, give the agent a file path and ask it to turn on reader mode. It stages the source without returning or sampling its body, then encounters only the next ordered passage through source_read and may attach ordinary, passage-grounded understanding before continuing. Codex also exposes $reading-mode; Claude Code exposes /reading-mode. Text pasted directly into chat has already been encountered, so use a file path when a genuinely fresh reading matters.
Codex is available through eligible ChatGPT plans, and Claude Code can use Claude Pro or Max. Their normal plan limits still apply.
The package ships both .codex-plugin and .claude-plugin manifests. The plugin combines the MCP capabilities with an understanding-work skill. While the mode is active, material, communicable understanding that could matter to the work or a future inquiry develops in the graph. The graph rolls a small state-dependent set of concrete next moves; the model judges their weights against the user task and freely chooses, combines, changes, or rejects them. The initializer above provides the same contract without waiting for a plugin-directory listing.
For Claude Code, the existing marketplace flow is:
# One-time: add the Emergent Wisdom marketplace
claude plugin marketplace add emergent-wisdom/marketplace
claude plugin install understanding-graph
For local development:
claude --plugin-dir /path/to/understanding-graph
This gives you the MCP server and these skills:
| Skill | Invoke | What it teaches |
|---|---|---|
| understanding-work | *(auto-loaded)* | Fluid graph-mediated understanding with weighted, model-chosen provocations |
| orient | /understanding-graph:orient | Read graph state at conversation start |
| quality-check | /understanding-graph:quality-check | Score, analyze, thermostat |
| reading-mode | /understanding-graph:reading-mode | Deep source reading with source_read |
| serendipity | /understanding-graph:serendipity | Inject novelty via grounded/pure serendipity |
| web-ui | /understanding-graph:web-ui | Launch 3D visualization at :3030 |
| graph-workflow | *(auto-loaded)* | Shared graph laws plus task-to-workflow routing |
| code-work | *(auto-loaded)* | Graph-native code nodes, generation, and executable evidence |
| collaborative-code | *(auto-loaded)* | Code-subtree ownership, handoffs, locks, and integration evidence |
| creative-work | *(auto-loaded)* | Books, prose, scripts, and editorial revision |
The raw MCP server works with any compatible client, but the bundled skill or generated project instructions are the recommended experience. Tool schemas alone do not reliably activate a multi-step understanding workflow.
This creates:
.codex/config.toml -- Codex MCP configuration.mcp.json -- Claude Code project MCP configurationAGENTS.md and CLAUDE.md -- the same canonical understanding workflow.agents/skills/reading-mode/SKILL.md -- explicit Codex reader workflow.claude/skills/reading-mode/SKILL.md -- explicit Claude Code reader workflow.gitignore entry for projects/ -- keeps graph data local; no starter project is createdEvery session opened in the directory shares the same project root. Once a named graph is selected, agents working there share it. Use additional agents only when the work has real independent seams.
Version 0.2.1 changes the authoring tool names. Existing graph data, including previously recorded notes, remains usable; this release requires no database schema migration.
graph_add_concept with graph_add_understanding; its parameters stay the same.graph_note with graph_add_understanding and a separate graph_connect operation in the same graph_batch. Map testimony to understanding and about to the connection's to target. Supply explicit title, trigger, and why values; these are required on the new node.attend to the next question or action when the node should remain open attention. Automatic resurfacing requires a learned_from edge to a visible document node; a provenance link alone does not enable it.For example, pass this to graph_batch, replacing SOURCE_NODE_ID with the existing passage or artifact node that occasioned the understanding:
{
"commit_message": "Record the unresolved retry assumption", "agent_name": "researcher", "operations": [ { "tool": "graph_add_understanding", "params": { "title": "Retries may synchronize clients", "trigger": "hypothesis", "understanding": "A fixed retry delay may align clients after a shared failure.", "why": "Questions whether the proposed recovery policy reduces overload", "attend": "Test fixed delays against jitter before choosing the policy." } }, { "tool": "graph_connect", "params": { "from": "$0.id", "to": "SOURCE_NODE_ID", "type": "learned_from", "why": "The hypothesis arose while reading this recovery design" } } ] }
Run npx -y understanding-graph@0.2.1 init in each initialized project to update managed MCP configuration and generated workflow guidance, then reconnect the MCP client so it loads the new tool catalog. Update custom configuration or instructions that the initializer preserves yourself.
If a client cannot install plugins or run the initializer, connect the MCP server directly:
claude mcp add ug -- npx -y understanding-graph@0.2.1 mcp
MCP initialization still supplies a concise graph-use contract, but client support for server instructions varies. For consistent behavior, also provide the bundled understanding-work skill or its generated project instructions.
Per-client setup guides: Claude Code · Claude Desktop · Cursor · mcporter
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": { "understanding-graph": { "command": "npx", "args": ["-y", "understanding-graph@0.2.1", "mcp"], "env": { "PROJECT_DIR": "/path/to/your/projects", "UG_SOURCE_ROOT": "/path/to/your/source-project" } } } }
UG_SOURCE_ROOT limits file-based source loading to that directory. The project initializer sets it to the project root automatically.
Add to your MCP config:
{
"mcpServers": { "understanding-graph": { "command": "npx", "args": ["-y", "understanding-graph@0.2.1", "mcp"], "env": { "PROJECT_DIR": "/path/to/your/projects" } } } }
The root npm package includes the built frontend and depends on the web server, so the published package can launch the UI directly:
PROJECT_DIR=/path/to/your/projects npx -y understanding-graph@0.2.1 start
Run independent sidecars by giving each process its own port and project-store root. The roots may be sibling directories on the same volume:
PORT=3101 PROJECT_DIR=/srv/undergraph/worker-1 npx -y understanding-graph@0.2.1 start
PORT=3102 PROJECT_DIR=/srv/undergraph/worker-2 npx -y understanding-graph@0.2.1 start
Use absolute paths in deployments. Sharing the installed package and its read-only frontend is safe; do not point independent sidecars at the same PROJECT_DIR.
The server binds to loopback by default. To run a worker on another host, explicitly set HOST and a private worker token; non-loopback startup fails closed without both:
HOST=0.0.0.0 PORT=3101 \
UG_WORKER_TOKEN=replace-with-a-long-random-secret \ PROJECT_DIR=/srv/undergraph/worker-1 \ npx -y understanding-graph@0.2.1 start
The trusted caller must send Authorization: Bearer on every /api or /admin request. Put remote traffic behind TLS or a private authenticated network.
To develop the UI from a checkout instead:
git clone https://github.com/emergent-wisdom/understanding-graph.git
cd understanding-graph npm install npm run build npm run start:web
冒頭だけを表示しています。続きはリポジトリで読めます