CogniLedger Makuri MCP Server
Public, read-only MCP server exposing structured metadata about the Makuri EdTech platform, including tools for platform info, languages, subjects, pricing, safety, compliance, tech stack, contact, free resources, and interactive panels. Designed for AI assistants to query platform details without accessing user data.
README
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 — 11 tools (9 info tools + 2 interactive MCP Apps panels), 3 markdown resources, and 2 guided prompts, covering mission, languages, teaching approach, pricing, safety, compliance posture, tech stack, contact channels, and free public learning resources.
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
- 11 tools returning static metadata (no database queries against user data), including 2 interactive MCP Apps panels that render inline in supporting hosts
- 3 markdown resources (manifesto, child-safety overview, connect guide) and 2 guided prompts
- 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 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. |
get_free_resources |
Free Makuri resources without registration: Slovarik vocabulary and the Romanian level test in two flavors (Quick Check, 20 questions, no email; Deep Diagnostic, 60 questions, email + certificate). |
show_how_makuri_works |
Interactive MCP Apps panel explaining the Makuri learning flow and ten action buttons (ui://makuri/how-it-works). |
show_romanian_quiz |
Interactive MCP Apps panel: Romanian mini-quiz that draws 10 random questions from a bank of 15 (levels A1–B2), RU/UK interface toggle, per-answer explanations, approximate level estimate, and CTA to the full free level test (ui://makuri/romanian-quiz). |
Resources
The server exposes three markdown documents via MCP resources/list / resources/read:
makuri://docs/manifesto— the founder-written manifesto on why Makuri exists.makuri://docs/safety-overview— child-safety design measures (account model, data minimization, AI behavior controls).makuri://docs/connect-guide— how to connect this server in ChatGPT, Claude, and Le Chat.
(The two interactive panels above are also exposed as resources at ui://makuri/how-it-works and ui://makuri/romanian-quiz, for hosts that support MCP Apps.)
Prompts
Two guided prompts via prompts/list:
evaluate_makuri_for_my_child(child_age, native_language)— guided fit evaluation for a specific child.makuri_safety_briefing()— honest safety briefing with explicit "design posture, not certified compliance" framing.
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 11 tools should be visible and callable, plus the 5 resources and 2 prompts.
Security and compliance
- No secrets in the repository.
.envis git-ignored;.env.examplelists 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.mdfor the full compliance posture.
License
MIT — see LICENSE.
Copyright © 2026 CogniLedger Solutions S.R.L.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.