moqui-mcp
Model Context Protocol (MCP) server enabling AI and LLM integration with the Moqui Framework.
Install / Use
claude mcp add nirendra10695 -- npx -y github:nirendra10695/moqui-mcpIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Tags
Our assessment of moqui-mcp
moqui-mcp scores 68/100 on our quality scale, 2743rd of 2,945 Automation skills we index.
Its MCP Server is 14 KB long, well organised into 34 sections and no code examples: a thorough specification that gives an agent plenty to work with.
It has 3 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 7 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- Our last check on 2026-09-12 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 69/100, with 4 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the first 100 KB of the file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-10-03. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
moqui-mcp compared with similar skills
All 4 of these similar skills score higher than moqui-mcp; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| moqui-mcp (this skill)by nirendra10695 | 68 | 3 | 7mo ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 88.6k | 17d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.3k | today | CLAUDE.md |
| rufloby ruvnet | 100 | 73.7k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.2k | today | CLAUDE.md |
Frequently asked questions
- How do I install moqui-mcp?
- Run
claude mcp add nirendra10695 -- npx -y github:nirendra10695/moqui-mcp. The install tabs above show the steps for each supported agent. - Which AI agents does moqui-mcp work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is moqui-mcp safe to use?
- Our scan of the first 100 KB of the file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It declares no license and scores 69/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is moqui-mcp still maintained?
- The repository was last updated about 7 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubMoqui MCP: Intelligent Automation for Enterprise Business
Transform Your ERP into an AI-Powered Command Center
Moqui MCP bridges the gap between cutting-edge AI and enterprise operations, enabling intelligent agents to interact directly with your business systems through the Model Context Protocol (MCP). Built on the robust Moqui Framework, this solution brings autonomous decision-making to every corner of your organization.
Enterprise-Grade Security: This powerful platform requires careful access control and proper authorization. Built on Moqui's proven security model, it ensures AI capabilities are deployed responsibly with full auditability.
🚀 Transform Your Business Operations
Intelligent Automation at Scale
- Smart Procurement: AI agents that analyze inventory, predict demand, and optimize purchasing decisions
- Dynamic Market Response: Real-time pricing adjustments based on supply chain data and market conditions
- Workforce Optimization: Intelligent scheduling and resource allocation powered by financial modeling
- Supply Chain Excellence: Automated coordination across global logistics networks
Data-Driven Decision Making
- Strategic Insights: AI-powered analysis of real sales trends and operational metrics
- Predictive Analytics: Financial forecasting grounded in actual business performance
- Proactive Risk Management: Continuous monitoring for anomalies, opportunities, and optimization
- Automated Compliance: Intelligent enforcement of business rules and regulatory requirements
The Future of Enterprise AI
- Collaborative AI Teams: Coordinated agents across Sales, Operations, Finance, and more
- Event-Driven Intelligence: Automated responses through Moqui's ECA/SECA framework
- Inter-Enterprise Coordination: AI agents that communicate and transact across organizational boundaries
- Digital Twin Simulations: Test and optimize strategies in a live business environment
Harness the Power of Agentic Architecture: Enterprise Resource Planning systems are naturally designed for role-based operations—HR, Sales, Production, Accounting each with distinct responsibilities and workflows. Moqui MCP transforms this organizational structure into an intelligent framework where AI agents assume authentic business personas, collaborate within established processes, and make decisions with real accountability. Your corporate hierarchy becomes the foundation for scalable AI automation.
From passive data systems to active business partners—AI that doesn't just analyze, but acts.
Overview
Moqui MCP creates a seamless bridge between AI assistants and your enterprise systems, transforming how intelligent agents interact with business operations. By implementing the Model Context Protocol (MCP), we've unlocked direct, secure access to Moqui's comprehensive service layer and entity model—giving AI the ability to not just read data, but to execute real business processes.
What This Means for You
Imagine AI that can:
- Execute Business Logic: Create orders, process invoices, manage inventory—all through natural conversation
- Query Any Data: Access your complete entity model with intelligent schema discovery
- Work Securely: Every action respects Moqui's battle-tested authorization system
- Scale Naturally: From simple queries to complex multi-step business workflows
Two Powerful Interaction Patterns
1. Service Tools: Business Operations as AI Functions
Moqui services become callable tools for AI agents. When you expose mantle.order.OrderServices.create#Order, the AI receives a complete JSON Schema definition including all parameters, types, and constraints. The agent can then create orders just like your application code does—with full validation, security checks, and business rule enforcement.
Example: An AI agent can analyze inventory levels, identify low stock items, find the best suppliers, and automatically generate purchase orders—all by calling exposed Moqui services.
2. Entity Resources: Your Data Model, Discoverable
Every entity in your Moqui system becomes an MCP resource. AI agents can:
- Discover what entities exist (
resources/list) - Learn entity schemas—fields, types, relationships (
resources/read) - Query data using Moqui's powerful entity engine
- Understand your business domain model automatically
Example: Ask "What customer fields are available?" and the AI reads the mantle.party.Party and mantle.party.Person schemas to understand your customer data structure.
The Result: AI agents that understand your business domain and can operate within it—like hiring an infinitely patient, perfectly compliant employee who never needs training.
Architecture & Implementation
Core Components
MoquiMcpServlet
The protocol gateway—handles JSON-RPC 2.0 communication between MCP clients (like Claude Desktop) and your Moqui instance. Manages WebSocket connections, session lifecycle, and message routing with full integration into Moqui's Visit tracking system.
McpServices
The intelligence layer that makes everything work:
mcp#Initialize: Negotiates MCP protocol capabilities, establishes secure sessionsmcp#ToolList: Dynamically discovers authorized services and generates tool definitions with complete JSON schemas. Includes smart filtering (like theforClaudeparameter) to handle client-specific constraintsmcp#ResourceList: Exposes your entity model as discoverable resourcesmcp#ResourceRead: Returns detailed entity schemas including fields, relationships, and indexesmcp#CallTool: Routes tool calls to actual Moqui services, handling parameter transformation and result packaging
Security Integration
This is where Moqui's artifact authorization system shines. Every service call, every entity query goes through the same security checks your applications use. If a user can't access mantle.account.PaymentServices through your UI, they can't access it through MCP either. Zero compromise on security.
Schema Intelligence
Moqui services can have complex parameter structures—nested Maps, Lists of objects, conditional requirements. Our schema generator recursively analyzes service definitions to produce accurate JSON Schema, including:
- Proper type mapping (Moqui types → JSON Schema types)
- Required vs optional parameters
- Nested object structures
- Array item types
- Enum values for status fields
Key Features Explained
🔧 Automatic Service Discovery Point the system at your component, and it finds all services the current user can access. No manual API definitions, no maintenance burden. As you add services, they automatically become available to AI agents (subject to authorization).
📚 Entity-as-Resource Pattern Following MCP's resource model, entities aren't just data—they're discoverable knowledge. AI agents can explore your schema, understand relationships, and learn your business domain organically.
🎯 Claude Desktop Ready
Some AI clients (looking at you, Claude) have tool name length limits. The forClaude parameter intelligently filters the tool list to stay within constraints while maximizing available functionality.
🔒 Security-First Design Built on Moqui's proven artifact authorization system. Every exposed service, every entity query, every tool call is subject to the same security rules that protect your web applications and APIs.
⚡ Session Continuity MCP sessions integrate with Moqui's Visit system, maintaining context across multiple interactions. The AI "remembers" what it's working on, just like a user session in your web app.
Why This Architecture Works
Moqui's service-oriented architecture is uniquely suited for AI integration:
- Self-Documenting: Service definitions include parameter metadata that generates perfect API schemas
- Transaction-Safe: Every service call runs in Moqui's transaction management system
- Event-Driven: SECA rules fire on AI actions just like user actions—full business logic preservation
- Multi-Tenant Ready: Organization filtering and data isolation work automatically
- Auditable: Every AI action flows through Moqui's audit logging system
Getting Started
Quick Setup
-
Clone into your Moqui runtime:
cd runtime/component git clone https://github.com/yourusername/moqui-mcp.git -
Configure your MCP client:
For Claude Desktop (requires mcp-remote as Claude only supports stdio mode):
Add to your Claude Desktop MCP settings (
~/Library/Application Support/Claude/claude_desktop_config.jsonon macOS):{ "mcpServers": { "moqui-mcp": { "command": "npx", "args": [ "-y", "mcp-remote@latest", "http://localhost:8080/mcp/", "--allow-http", "--header", "Authorization:Basic ${AUTH_TOKEN}", "--header", "Content-Type:application/json", "--header", "Accept:application/json" ], "env": { "AUTH_TOKEN": "<your-base64-token>" } } } }Note: The
AUTH_TOKENis the Base64 encoding ofusername:password. Generate yours with:echo -n "your-username:your-password" | base64For GitHub Copilot:
Add to your Copilot MCP settings:
{ "servers": { "moqui-mcp": { "type": "http", "url": "http://localhost:8080/mcp/", "requestInit": { "headers": { "Authorization": "Basic <your-base64-token>" } } } } }Replace
<your-base64-token>with your Base64-encodedusername:password. -
Start exploring:
- Ask AI to list available tools: "What services can you access?"
- Query your data model: "Show me the Order entity schema"
- Execute business operations: "Create a test order for customer ACME"
Testing & Development
The component includes a comprehensive test suite in test/. Contributions are welcome! If you're building new features or fixing bugs, please add tests.
Real-World Use Cases
Intelligent Customer Service
AI agents can look up orders, check shipment status, process returns, and update customer information—all through natural language while respecting your security policies.
Automated Procurement
Agents monitor inventory levels, analyze supplier performance, and generate purchase orders when stock falls below thresholds—operating within your defined business rules.
Financial Operations
From invoice processing to payment reconciliation, AI can handle routine financial tasks while maintaining full audit trails and compliance requirements.
Data Analysis & Reporting
Instead of building custom dashboards, let AI query your entity model directly to answer business questions: "Which products had the highest returns last quarter?"
License
This project is released into the public domain under CC0 1.0 Universal plus a Grant of Patent License, maintaining consistency with the Moqui Framework licensing philosophy. Use it freely, modify it as needed, build commercial products with it—no strings attached.
Related Projects & Resources
Essential Reading
- Moqui Framework - The foundation this builds upon. If you're new to Moqui, start here.
- MCP Specification - Understand the protocol that enables AI integration
- Mantle Business Artifacts - The business service layer that powers most MCP tools
Complementary Projects
- MarbleERP - Full ERP component for Moqui, p
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
