GLM-4.6 MCP Server
Enterprise Architecture Consultation Protocol
Model Context Protocol bridge enabling Claude 4.5 Sonnet to leverage GLM-4.6's architectural intelligence for advanced system design, scalability patterns, and technical decision-making.
🏗️ System Overview
This MCP server establishes a bi-directional protocol bridge between Claude 4.5 Sonnet and GLM-4.6, enabling real-time architectural consultation during development workflows. The server exposes GLM-4.6's specialized capabilities through standardized MCP tools, facilitating seamless integration with Warp Terminal's agent infrastructure.
Architectural Capabilities
- Distributed Systems Design: Microservices patterns, service mesh architectures, event-driven systems
- Scalability Engineering: Horizontal scaling strategies, load balancing, caching hierarchies
- Security Architecture: Threat modeling, zero-trust patterns, authentication/authorization frameworks
- Code Analysis: SOLID principles evaluation, design pattern recognition, refactoring recommendations
- Technical Decision Review: Trade-off analysis, risk assessment, alternative approach evaluation
- System Architecture Design: Component decomposition, data flow modeling, technology stack selection
⚡ Quick Start
Prerequisites
node >= 18.0.0
npm >= 9.0.0
GLM-4.6 API Key from https://open.bigmodel.cn
Installation
cd glm-mcp-server
npm install
npm run build
Environment Configuration
Create .env file in project root:
GLM_API_KEY=your_api_key_here
Security Notice: Never commit .env to version control. Use secure secret management in production environments.
🔧 Warp Terminal Integration
MCP Server Configuration
Add the following configuration to your Warp MCP servers configuration file:
Location: ~/.config/warp-terminal/mcp_servers.json or Warp Settings → MCP Servers
{
"mcpServers": {
"glm-architecture": {
"command": "node",
"args": ["/absolute/path/to/glm-mcp-server/build/index.js"],
"env": {
"GLM_API_KEY": "your_glm_api_key_here"
}
}
}
}
⚠️ Configuration Notes:
- Replace
/absolute/path/to/glm-mcp-serverwith your actual installation path - Replace
your_glm_api_key_herewith your actual GLM API key - Restart Warp Terminal after configuration changes
Verification
# Test server functionality
node build/index.js
# Expected output: "GLM-4.6 MCP Server running on stdio"
📡 MCP Tools Reference
1. consult_architecture
General architectural consultation for system design patterns, scalability strategies, and technical guidance.
Input Schema:
{
query: string; // Architectural question requiring expert consultation
context?: string; // Optional system context, requirements, constraints
}
Use Case: High-level architectural decisions, pattern selection, scalability planning
2. analyze_code_architecture
Architectural analysis of source code including design patterns, SOLID principles, and improvement recommendations.
Input Schema:
{
code: string; // Source code to analyze
language: string; // Programming language (typescript, python, go, java, etc.)
question: string; // Specific architectural question about the code
}
Use Case: Code review, refactoring planning, design pattern evaluation
3. design_system_architecture
Complete system architecture design from requirements including component breakdown, data flow, and deployment strategies.
Input Schema:
{
requirements: string; // Detailed system requirements, constraints, objectives
}
Use Case: New system design, architecture documentation, technology selection
4. review_technical_decision
Technical decision review with impact assessment, trade-off analysis, and alternative recommendations.
Input Schema:
{
decision: string; // Technical decision to review
context: string; // Current architecture, constraints, objectives
}
Use Case: Architecture review, technology evaluation, risk assessment
🔬 Usage Examples
Example 1: Architectural Consultation
Within Warp Terminal, Claude can invoke:
// Claude automatically calls via MCP
consult_architecture({
query: "What's the optimal caching strategy for a high-traffic API with 10k req/s?",
context: "Node.js microservices, PostgreSQL database, AWS infrastructure"
})
Example 2: Code Architecture Analysis
analyze_code_architecture({
code: `class UserService { ... }`,
language: "typescript",
question: "Does this service follow clean architecture principles?"
})
Example 3: System Design
design_system_architecture({
requirements: `
- Real-time messaging platform
- 1M concurrent users
- Sub-100ms latency
- 99.99% uptime SLA
- Global distribution
`
})
🏛️ Architecture
┌─────────────────────────────────────────────────────────────┐
│ Warp Terminal │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ Claude 4.5 Sonnet Agent │ │
│ └────────────────────┬─────────────────────────────────┘ │
└───────────────────────┼─────────────────────────────────────┘
│ MCP Protocol (stdio)
▼
┌─────────────────────────────────────────────────────────────┐
│ GLM MCP Server (Node.js) │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ MCP Protocol Handler │ Tool Registry │ │
│ ├──────────────────────────────────────────────────────┤ │
│ │ GLM-4.6 API Client Layer │ │
│ │ • Authentication • Error Handling • Retry Logic │ │
│ └──────────────────────────────────────────────────────┘ │
└────────────────────────┬────────────────────────────────────┘
│ HTTPS/REST
▼
┌─────────────────────────────────────────────────────────────┐
│ GLM-4.6 API (open.bigmodel.cn) │
│ Zhipu AI Model Inference │
└─────────────────────────────────────────────────────────────┘
🛠️ Development
Build
npm run build # Compile TypeScript to JavaScript
npm run watch # Development mode with auto-rebuild
Project Structure
glm-mcp-server/
├── src/
│ ├── index.ts # MCP server entry point
│ └── glm-client.ts # GLM-4.6 API client
├── build/ # Compiled JavaScript output
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript configuration
└── .env # Environment variables (not in VCS)
🔐 Security Considerations
- API Key Management: Store GLM_API_KEY in environment variables, never in code
- Transport Security: All API communications use HTTPS/TLS
- Input Validation: All tool inputs are validated before processing
- Error Handling: Sensitive information is sanitized from error messages
- Rate Limiting: Implement client-side rate limiting for production deployments
📊 Performance Characteristics
| Metric | Specification |
|---|---|
| Latency | 2-8s (model inference dependent) |
| Throughput | API key tier dependent |
| Timeout | 60s default (configurable) |
| Max Token Output | 4096 tokens |
| Concurrent Requests | Single instance: 1 (sequential processing) |
🐛 Troubleshooting
Server Not Starting
# Verify Node.js version
node --version # Must be >= 18.0.0
# Check build output
npm run build
# Verify GLM_API_KEY is set
echo $GLM_API_KEY
API Authentication Errors
- Verify API key validity at https://open.bigmodel.cn
- Check API key has sufficient quota
- Ensure no whitespace in
.envfile
Warp Terminal Integration Issues
- Restart Warp Terminal after configuration changes
- Verify absolute path in MCP configuration
- Check Warp logs: Warp → Settings → Advanced → View Logs
📚 Resources
- GLM-4.6 Documentation: https://docs.z.ai/guides/llm/glm-4.6
- Model Context Protocol: https://modelcontextprotocol.io
- Warp MCP Integration: https://docs.warp.dev/features/agent-mode/model-context-protocol
📝 License
MIT License - Copyright (c) 2025 CyberLink Security
🤝 Support
Enterprise Support: info@cyberlinksec.com
Issue Reporting: Include server logs, Warp version, and reproduction steps
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