GLM-4.6 MCP Server

GLM-4.6 MCP Server

Enables Claude to consult GLM-4.6's architectural intelligence for system design, code analysis, scalability patterns, and technical decision-making. Provides specialized tools for enterprise architecture consultation, distributed systems design, and code review through the Model Context Protocol.

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GLM-4.6 Language Models

<span style="color: #1e3a8a">GLM-4.6 MCP Server</span>

<span style="color: #10b981">Enterprise Architecture Consultation Protocol</span>

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.

License: MIT Node.js TypeScript


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<span style="color: #1e3a8a">🏗️ System Overview</span>

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.

<span style="color: #10b981">Architectural Capabilities</span>

  • 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

<span style="color: #1e3a8a">⚡ Quick Start</span>

<span style="color: #10b981">Prerequisites</span>

node >= 18.0.0
npm >= 9.0.0
GLM-4.6 API Key from https://open.bigmodel.cn

<span style="color: #10b981">Installation</span>

cd glm-mcp-server
npm install
npm run build

<span style="color: #10b981">Environment Configuration</span>

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.


<span style="color: #1e3a8a">🔧 Warp Terminal Integration</span>

<span style="color: #10b981">MCP Server Configuration</span>

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-server with your actual installation path
  • Replace your_glm_api_key_here with your actual GLM API key
  • Restart Warp Terminal after configuration changes

<span style="color: #10b981">Verification</span>

# Test server functionality
node build/index.js
# Expected output: "GLM-4.6 MCP Server running on stdio"

<span style="color: #1e3a8a">📡 MCP Tools Reference</span>

<span style="color: #10b981">1. consult_architecture</span>

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


<span style="color: #10b981">2. analyze_code_architecture</span>

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


<span style="color: #10b981">3. design_system_architecture</span>

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


<span style="color: #10b981">4. review_technical_decision</span>

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


<span style="color: #1e3a8a">🔬 Usage Examples</span>

<span style="color: #10b981">Example 1: Architectural Consultation</span>

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"
})

<span style="color: #10b981">Example 2: Code Architecture Analysis</span>

analyze_code_architecture({
  code: `class UserService { ... }`,
  language: "typescript",
  question: "Does this service follow clean architecture principles?"
})

<span style="color: #10b981">Example 3: System Design</span>

design_system_architecture({
  requirements: `
    - Real-time messaging platform
    - 1M concurrent users
    - Sub-100ms latency
    - 99.99% uptime SLA
    - Global distribution
  `
})

<span style="color: #1e3a8a">🏛️ Architecture</span>

┌─────────────────────────────────────────────────────────────┐
│                      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                       │
└─────────────────────────────────────────────────────────────┘

<span style="color: #1e3a8a">🛠️ Development</span>

<span style="color: #10b981">Build</span>

npm run build      # Compile TypeScript to JavaScript
npm run watch      # Development mode with auto-rebuild

<span style="color: #10b981">Project Structure</span>

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)

<span style="color: #1e3a8a">🔐 Security Considerations</span>

  • 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

<span style="color: #1e3a8a">📊 Performance Characteristics</span>

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)

<span style="color: #1e3a8a">🐛 Troubleshooting</span>

<span style="color: #10b981">Server Not Starting</span>

# 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

<span style="color: #10b981">API Authentication Errors</span>

  • Verify API key validity at https://open.bigmodel.cn
  • Check API key has sufficient quota
  • Ensure no whitespace in .env file

<span style="color: #10b981">Warp Terminal Integration Issues</span>

  • Restart Warp Terminal after configuration changes
  • Verify absolute path in MCP configuration
  • Check Warp logs: Warp → Settings → Advanced → View Logs

<span style="color: #1e3a8a">📚 Resources</span>

  • 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

<span style="color: #1e3a8a">📝 License</span>

MIT License - Copyright (c) 2025 CyberLink Security


<span style="color: #1e3a8a">🤝 Support</span>

Enterprise Support: info@cyberlinksec.com

Issue Reporting: Include server logs, Warp version, and reproduction steps


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<span style="color: #10b981">Built with Enterprise Standards by CyberLink Security</span>

Empowering AI-Driven Architecture Decision Intelligence

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