Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Persistent understanding via workflow prompts, typed updates, graph-native code, and supersession.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"understanding-graph": {
"command": "npx",
"args": [
"-y",
"understanding-graph",
"mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add understanding-graph -- npx -y understanding-graph mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"understanding-graph": {
"command": "npx",
"args": [
"-y",
"understanding-graph",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"understanding-graph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"understanding-graph",
"mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 emergent-wisdom 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.2.1)은 8일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Toggl 2.0
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
Toggl 2.0 MCP server for tasks, projects, time entries, and workspace operations.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요