CogniLedger MCP Server — Makuri showcase

A public, read-only Model Context Protocol server operated by CogniLedger Solutions S.R.L. (Bucharest, Romania). It exposes structured metadata about the Makuri EdTech platform — eight tools covering mission, languages, teaching approach, pricing, safety, compliance posture, tech stack, and contact channels.

This is a reference deployment demonstrating production MCP patterns under EU compliance constraints. Makuri is a High Risk AI system under EU AI Act Annex III, paragraph 3 (educational AI for minors); the v1 scope of this server is therefore deliberately narrow: metadata only, no user data, no PII, no aggregated analytics.

• Production endpoint: https://mcp.cogniledger.eu/mcp
• License: MIT
• Repository: github.com/cogniledger/cogniledger-mcp-makuri
• Contact: leonid@cogniledger.eu

What this server is

• Public, unauthenticated, read-only
• Eight tools returning static metadata (no database queries against user data)
• Designed to be called by AI assistants — Claude Desktop, Le Chat (Mistral), Cursor, ChatGPT Apps SDK, and any other MCP-capable client

What this server is not

• It is not the Makuri product. End users of Makuri (children, parents) interact with makuri.eu, not this MCP server.
• It does not expose user data, PII, IP addresses, behavioral analytics, or any data derived from end-user activity.

Connect

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "cogniledger-makuri": {
      "url": "https://mcp.cogniledger.eu/mcp"
    }
  }
}

Restart Claude Desktop. The eight tools appear under the connector picker.

Le Chat (Mistral)

In Le Chat settings, add a new MCP connector:

• Name: CogniLedger — Makuri
• Transport: streamable-http
• URL: https://mcp.cogniledger.eu/mcp

Cursor

Edit ~/.cursor/mcp.json:

{
  "mcpServers": {
    "cogniledger-makuri": {
      "url": "https://mcp.cogniledger.eu/mcp"
    }
  }
}

Tools

Tool	Description
get_platform_info	Mission, target users, founding details, operating company.
get_supported_languages	All 14 supported locales with UI / AI tutor coverage flags. Optional locale filter.
get_subjects	Textbook-agnostic teaching approach, ten action buttons, learning modes.
get_pricing_tiers	Free trial and beta subscription details.
get_safety_features	Age gate, content filters, parental controls, AI safety guardrails.
get_compliance_matrix	EU AI Act, GDPR, GDPR-K, COPPA, ISO 42001 — current status with disclaimer. Optional regulation filter.
get_tech_stack	Frontend, backend, database, AI providers, EU data residency.
get_contact_info	Contact channels by purpose. Optional purpose filter.

Full input schemas and example responses: docs/TOOLS.md. Real client transcripts: docs/EXAMPLES.md. Compliance disclosure: docs/COMPLIANCE_DISCLOSURE.md.

Local development

git clone https://github.com/cogniledger/cogniledger-mcp-makuri.git
cd cogniledger-mcp-makuri
npm install
npm run dev

The server starts on http://localhost:3000. The MCP endpoint is http://localhost:3000/mcp.

Smoke test

# In one terminal:
npm run dev

# In another:
npm run test:smoke

The smoke test connects to the local server, lists tools, calls each one, and exits non-zero on any failure.

MCP Inspector

npx @modelcontextprotocol/inspector

Connect with transport streamable-http to http://localhost:3000/mcp. All eight tools should be visible and callable.

Security and compliance

• No secrets in the repository. .env is git-ignored; .env.example lists variable names only and is empty for v1.
• No outbound API calls, no database queries, no authentication. v1 is pure static-data read.
• Per-tool structured logging emits one JSON line per invocation with five fields only: evt, tool, ts, status, duration_ms. No request bodies, no IPs, no argument values.
• See docs/COMPLIANCE_DISCLOSURE.md for the full compliance posture.

License

MIT — see LICENSE.

Copyright © 2026 CogniLedger Solutions S.R.L.