Openemis

title: "openemis-mcp — AI bridge for OpenEMIS school management" description: "Free, read-only MCP server that connects AI assistants to OpenEMIS school management. Query student attendance, risks, staff, and 678 resources." keywords:

• OpenEMIS
• school management system
• education management
• student attendance
• student risks
• MCP server

openemis-mcp — AI bridge for OpenEMIS school management

Free, read-only MCP bridge between AI agents and any OpenEMIS school.

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 gives AI agents read-only access to the data in any OpenEMIS school so you can ask questions in plain English and get answers in seconds.

Built on the published OpenEMIS Core API (reference: api.openemis.org/core) and verified against the public demo at demo.openemis.org/core.

What this is: openemis-mcp is a free MCP server that connects AI assistants (Claude, Cursor, Codex) to the OpenEMIS school management system. It exposes 678 resources — students, student attendance, student risks, staff, exams, infrastructure — across 26 curated read-only playbooks, plus 14 redirect stubs for write operations.

Ask in plain English:

*"How many current students are at Avory Primary?"*

The agent plans the calls, this MCP delivers the data:

*"Avory Primary School has 97 currently enrolled students across 6 classes."*

No code. No JSON. Just ask.

What's included (free, MIT)

26 read-only playbooks covering attendance, assessment, student profiles, staff profiles, infrastructure, meals, risk dashboards, class reports, timetables, audit logs, school accreditation / registration, admission and enrolment queue state, and a primer on how the OpenEMIS workflow plugin powers every multi-step approval — each verified against the v5 manifest at 100% resource coverage. 14 additional playbook stubs are discoverable here but redirect to [openemis-mcp-pro](https://github.com/tixuz/openemis-mcp-pro) for the actual write/auth steps.

Translations: Русский · Español · हिन्दी · العربية — the original 17 view playbooks also translated in all four languages; 9 newer playbooks (added in v1.1.0 for Core 5.10.0, plus the two workflow playbooks) are English-only for now.

✏️ Write operations (creating/updating records in OpenEMIS) require [openemis-mcp-pro](https://github.com/tixuz/openemis-mcp-pro). This free server is intentionally read-only — post, put, and delete are not available.

What's in Pro

openemis-mcp-pro adds write tools, remote hosting, and ChatGPT compatibility on top of this free read-only server.

HTTP server mode lets you install Pro once on an Oracle Always Free ARM instance and connect from any device — no per-machine setup. The built-in OpenAPI adapter means teachers can use ChatGPT (or any AI assistant) to mark attendance and look up student records by importing a single schema URL. See the ChatGPT Teacher Guide for step-by-step setup.

→ Pricing: khindol.madraimov@gmail.com

Install

Requires Node 22+.

git clone https://github.com/tixuz/openemis-mcp.git

cd openemis-mcp npm install npm run build cp .env.example .env $EDITOR .env

Configure

OPENEMIS_BASE_URL=https://demo.openemis.org/core

OPENEMIS_USERNAME=admin OPENEMIS_PASSWORD=your_password OPENEMIS_API_KEY=your_api_key

Smoke test

set -a && source .env && set +a

node scripts/smoke-login.mjs

Register with Claude Code

claude mcp add openemis \

--env OPENEMIS_BASE_URL="https://your-instance/core" \ --env OPENEMIS_USERNAME="…" \ --env OPENEMIS_PASSWORD="…" \ --env OPENEMIS_API_KEY="…" \ -- node "$(pwd)/dist/server.js"

Works with any MCP-compatible client: Claude Code, Cursor, Cline, Codex (via gemmy-and-qwenny), or any stdio MCP client.

Verbose logging (optional)

Capture every tool call and its response as JSONL — useful for debugging, tuning playbooks, or sharing a bug report.

# stderr (visible in your MCP client's log panel)

OPENEMIS_LOG_VERBOSE=1 node dist/server.js

write to a file

OPENEMIS_LOG_VERBOSE=1 OPENEMIS_LOG_FILE=/tmp/openemis.jsonl node dist/server.js

Each line is a JSON object: {ts, type:"tool_call"|"tool_result"|"tool_error", tool, args?, result?, latency_ms, ...}. Credential-shaped keys (password, authorization, api_key, token, secret) are redacted automatically.

⚠️ Privacy: tool_result entries contain the actual OpenEMIS data returned to the agent — student names, staff IDs, enrollment details. Enable only on instances you own, or with explicit consent. Default is OFF.

🌐 Remote / server install: openemis-mcp-pro adds an HTTP server mode — install once on Oracle Always Free and every AI assistant (Claude Code, Cursor, ChatGPT) connects by URL with no per-machine setup. See the ChatGPT Teacher Guide for how to let teachers mark attendance via ChatGPT.

Playbooks

24 read-only workflow guides — see docs/playbooks/. Write-side playbooks (mark attendance, enrol a student, set school accreditation, etc.) are discoverable here as stubs that point at [openemis-mcp-pro](https://github.com/tixuz/openemis-mcp-pro).

Read playbooks (school data lookups)

| 15 | [View Institution Meals](docs/playbooks/view-instituti