Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
제작자가 쓴 설명(영어 원문)
Read + write MCP server for OpenEMIS — free open-source school management system. 675 resources.
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.
OPENEMIS_BASE_URL, OPENEMIS_API_KEY, OPENEMIS_USERNAME, OPENEMIS_PASSWORD, OPENEMIS_TIMEOUT_MS, OPENEMIS_CORE_IN_OPERATOR비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
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": {
"openemis-pro": {
"command": "npx",
"args": [
"-y",
"openemis-mcp-pro"
],
"env": {
"OPENEMIS_BASE_URL": "your-value",
"OPENEMIS_API_KEY": "your-value",
"OPENEMIS_USERNAME": "your-value",
"OPENEMIS_PASSWORD": "your-value",
"OPENEMIS_TIMEOUT_MS": "your-value",
"OPENEMIS_CORE_IN_OPERATOR": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add openemis-pro --env OPENEMIS_BASE_URL=your-value --env OPENEMIS_API_KEY=your-value --env OPENEMIS_USERNAME=your-value --env OPENEMIS_PASSWORD=your-value --env OPENEMIS_TIMEOUT_MS=your-value --env OPENEMIS_CORE_IN_OPERATOR=your-value -- npx -y openemis-mcp-pro실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"openemis-pro": {
"command": "npx",
"args": [
"-y",
"openemis-mcp-pro"
],
"env": {
"OPENEMIS_BASE_URL": "your-value",
"OPENEMIS_API_KEY": "your-value",
"OPENEMIS_USERNAME": "your-value",
"OPENEMIS_PASSWORD": "your-value",
"OPENEMIS_TIMEOUT_MS": "your-value",
"OPENEMIS_CORE_IN_OPERATOR": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"openemis-pro": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"openemis-mcp-pro"
],
"env": {
"OPENEMIS_BASE_URL": "your-value",
"OPENEMIS_API_KEY": "your-value",
"OPENEMIS_USERNAME": "your-value",
"OPENEMIS_PASSWORD": "your-value",
"OPENEMIS_TIMEOUT_MS": "your-value",
"OPENEMIS_CORE_IN_OPERATOR": "your-value"
}
}
}
}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.
OPENEMIS_USERNAME envOPENEMIS_TIMEOUT_MS envOPENEMIS_CORE_IN_OPERATOR env이 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 tixuz 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.
입력해야 할 값: OPENEMIS_BASE_URL, OPENEMIS_API_KEY, OPENEMIS_PASSWORD
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(1.1.0)은 6개월 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, Whisper
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.
One routable IPv6 per AI agent, verifiable from the DNS root. Keyless tools need no signup.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
title: openemis-mcp-pro — Read + Write MCP Server for OpenEMIS School Management description: openemis-mcp-pro is the read and write MCP server that bridges AI assistants to the OpenEMIS school management information system — 678 resources, 3361 endpoints, 40 playbooks. keywords:
A natural-language bridge between MCP-aware agents (Claude, Codex, Cursor, etc.) and any OpenEMIS school — with full read + write access.
OpenEMIS is a free, open-source school management information system developed by UNESCO and KORDIT. It runs the day-to-day administration of every kind of educational institution — kindergartens, primary schools, secondary schools, secondary vocational institutions, technical colleges, and universities — managing students, staff, attendance, assessment, infrastructure, meals, scholarships, examinations, training, and ministry-level reporting. This MCP-pro server adds full read + write access plus per-user authentication on top of any OpenEMIS school.
Translations: Русский · Español · हिन्दी · العربية
Built on top of the published OpenEMIS Core API (reference docs at api.openemis.org/core) and verified end-to-end against the public demo at [demo.openemis.org/core](https://demo.openemis.org/core) with real credentials, real data, real round-trips.
Ask in English:
*"How many current students are at Avory Primary?"*
The agent plans the calls, this MCP delivers the data, and you get the answer:
*"Avory Primary School (code P1002) has 553 currently enrolled students."*
You never write a line of code. You never see JSON. You just ask.
Status: v1.0.0 — full CRUD for non-workflow resources. Read queries work against every OpenEMIS v5 resource. Write tools (create/update/delete) are live for all resources that do not flow through the CakePHP Workflow plugin. Workflow-controlled resources (attendance, staff leave) are blocked at the tool level and redirect to the appropriate playbook.
openemis-mcp-pro is the read + write MCP server that connects AI assistants to the OpenEMIS school management system. It exposes 678 resources (students, attendance, risks, staff, exams, infrastructure) across 40 curated playbooks — 26 read and 14 write/auth. The pro distribution adds direct write tools (openemis_create, openemis_update, openemis_delete), HTTP server mode for ChatGPT Custom GPT, and per-user authentication on top of the free read-only distribution.
The OpenEMIS Core REST API is large — the v5 surface alone exposes 3,361 endpoints across 678 resources (Core 5.13.0). No AI agent can hold that in context, and raw Swagger-style introspection floods a conversation with noise that has nothing to do with the user's actual question.
This MCP solves that in two ways:
openemis_discover(topic) tool narrows to the ~20–30 endpoints relevant to what the user is actually asking about ("attendance", "students", "assessment") — powered by a small curated knowledge pack of Domain-*.md notes.openemis_get tool covers list + singleton + filtered search across every resource. The agent supplies resource + optional id + optional params (_fields, _conditions, orderby, page, limit) and the rest of the OpenEMIS CakePHP-style query DSL maps straight through.The net effect: agents answer natural-language questions in 2–4 tool calls, not 30.
| Tool | Since | What it does |
|---|---|---|
openemis_health | v0.1 | Pings the configured instance and reports reachability. Performs a real login round-trip — if this passes, CRUD will work. |
openemis_list_domains | v0.1 | Lists the curated OpenEMIS domains — Attendance, Assessment, Staff, Student, Institution, Schedule, Examination, Report — each with a one-line summary. The agent uses this to figure out *where* a question lives. |
openemis_discover | v0.1 | Input: a topic string. Output: up to 30 endpoints relevant to that topic, drawn from the domain knowledge pack and the per-instance manifest. Keeps conversations small regardless of how large the underlying API is. |
openemis_list_playbooks | v0.2 | Lists all 40 curated workflow playbooks with id, title, domain, and audience. The agent uses this to find the right step-by-step guide for a user-level task. |
openemis_get_playbook | v0.2 | Input: a playbook id. Output: the full playbook — resources, ordered steps, guidance notes, and example queries. |
openemis_get | v0.1 | Unified read tool. { resource, id?, params? } — if id is present, fetches the singleton; otherwise lists with any combination of _fields, _conditions, orderby, order, page, limit, plus any ad-hoc filter key. |
openemis_create | v0.3.0 | Create a new record. { resource, body } — non-workflow resources only. Workflow-controlled resources (e.g. institution-staff-leave) are blocked and will redirect to the appropriate playbook. |
openemis_update | v0.3.0 | Update an existing record by id. { resource, id, body } — non-workflow resources only. |
openemis_delete | v0.3.0 | Delete a record by id. { resource, id } — non-workflow resources only. |
A representative natural-language question like *"how many teachers at Avory Primary, how many vacant positions?"* resolves to three openemis_get calls — chained by the agent, narrowed by _conditions, delivered back as a single English answer. A write request like *"enrol a new student"* uses openemis_get_playbook to load the step-by-step guide, then openemis_create for each write step.
Tested against OpenEMIS Core 5.13.0 (master, June 2026). Earlier 5.7 – 5.12 deployments are also supported — the API surface is backwards-compatible.
openemis_get accepts params.ids = "1,2,3" for batch lookups. Core 5.10+ carries POCOR-9660 (?id=1,2,3 and _conditions= :IN(...) support in CrudApiController), so the handler collapses the batch into a single round-trip by default. Pointing at an older Core (5.7 – 5.9) without the native operator? Force the legacy parallel fan-out:
OPENEMIS_CORE_IN_OPERATOR=off
For composite-PK or view resources — where ids does not apply — use _conditions= :IN(1,2,3) instead; it filters any field by a value list and works regardless of this flag. Filtering on a field that does not exist on a resource now returns HTTP 400 (Core 5.10+, POCOR-9697), so use exact field names.
Every claim in this README was proven against the public demo instance before being written:
POST /api/v5/login with { username, password, api_key } → JWT cached, 331 charsGET /api/v5/institutions?limit=200&_fields=id,name,code → 24 institutions incl. "Avory Primary School" (id=6, code P1002)GET /api/v5/institution-students?institution_id=6&student_status_id=1&limit=1 → pagination reports last_page: 553 → 553 currently enrolled studentsGET /api/v5/academic-periods → 7 pages of real academic-year dataGET /api/v5/absence-types → EXCUSED, UNEXCUSED, LATE, etc.The sample scripts/smoke-login.mjs shipped with this repo performs the login test step-by-step so you can confirm reachability against your own instance before wiring it into Claude Code.
openemis-mcp speaks the Model Context Protocol over stdio — any MCP-compatible client works:
Stdio mode (local machine) — connects as a subprocess:
| Agent | How to connect |
|---|---|
Claude Code (claude CLI) | claude mcp add — primary tested client, all 9 tools available |
| Cursor | Add to .cursor/mcp.json — full tool access |
| Cline / Continue (VS Code) | Add server in MCP settings |
| Codex | Via gemmy-and-qwenny bridge |
| Any MCP client | Point at node dist/server.js with env vars set |
HTTP server mode (OPENEMIS_TRANSPORT=http, install once on Oracle/VPS) — connects by URL:
| Client | How to connect |
|---|---|
| Claude Code (remote) | claude mcp add --transport http --url http://your-server:3000/mcp --header "Authorization: Bearer " |
| Cursor / Cline | Add remote MCP URL in settings |
| ChatGPT (Custom GPT) | Import schema from http://your-server:3000/openapi.json → Actions → Bearer token |
| Any HTTP client | REST API at /api/* — see Teacher Guide |
Requires Node 22+ (for built-in fetch and AbortController) and Python 3.10+ (for the manifest builder and playbook generator scripts in mcp-openemis-gen/). The MCP server itself is Node-only; Python is only needed if you rebuild the manifest from source.
git clone https://github.com/tixuz/openemis-mcp.git
cd openemis-mcp
npm install npm run build
cp .env.example .env $EDITOR .env
.env.example documents every variable. At minimum you need the three credentials your OpenEMIS admin issues:
OPENEMIS_BASE_URL=https://demo.openemis.org/core # or your own instance
OPENEMIS_USERNAME=admin OPENEMIS_PASSWORD=your_password OPENEMIS_API_KEY=your_api_key
OPENEMIS_TIMEOUT_MS=30000 OPENEMIS_VAULT_PATH=/absolute/path/to/domain-notes OPENEMIS_MANIFEST_PATH=/absolute/path/to/manifest.jsonl
The server logs in lazily on the first authenticated tool call, POSTing to /api/v5/login, parsing the JWT out of data.token, and caching it in memory. On a 401 it re-logs in and retries once.
OPENEMIS_VAULT_PATH points at the folder containing the curated Domain-*.md notes used by openemis_discover. If missing, discovery degrades gracefully to keyword matching against the manifest alone.
OPENEMIS_MANIFEST_PATH points at the JSONL output of the companion builder in ../mcp-openemis-gen/. If absent, the discovery tools return a friendly "manifest not built yet" hint — they don't crash.
set -a && source .env && set +a
node scripts/smoke-login.mjs
Expected:
[Test] Loading config...
[OK] Config loaded: baseUrl=https://demo.openemis.org/core [Test] Creating client... [OK] Client created [Test] Attempting login... [OpenEMIS] Login successful; cached JWT (331 chars) [OK] Login successful
claude mcp add openemis \
--env OPENEMIS_BASE_URL="https://your-openemis/core" \ --env OPENEMIS_USERNAME="…" \ --env OPENEMIS_PASSWORD="…" \ --env OPENEMIS_API_KEY="…" \ --env OPENEMIS_VAULT_PATH="/absolute/path/to/vault" \ -- node "$(pwd)/dist/server.js"
claude mcp list | grep openemis
Any new Claude Code session in this project will see all nine tools automatically.
Set OPENEMIS_TRANSPORT=http to run as a persistent HTTP server instead of a local subprocess. Install once on your server; every MCP-compatible client (Claude Code, Cursor, Cline, Windsurf) connects by URL.
On your server:
git clone https://github.com/tixuz/openemis-mcp-pro.git
cd openemis-mcp-pro npm install && npm run build cp .env.example .env $EDITOR .env
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요