Ccglm FAQs

Question 1

Does Ccglm offer enhanced security for AI interactions?

Accepted Answer

Yes, security is a core feature. Ccglm ensures token protection by storing them in git-ignored `.env` files, performs automatic log sanitization to redact sensitive information, and uses environment isolation for subprocesses to enhance overall security.

Question 2

What are the primary capabilities of Ccglm?

Accepted Answer

Ccglm excels at several key developer tasks: advanced code generation with automatic file tracking, deep code analysis with configurable timeouts up to 40 minutes, and handling general AI-powered queries via the GLM-4.6 model.

Question 3

What is Ccglm and how does it integrate with Claude Code?

Accepted Answer

Ccglm is an MCP server designed to seamlessly integrate Z.AI's powerful GLM-4.6 models into your existing Claude Code environment. It allows Claude Code (using Anthropic Sonnet) to invoke GLM-4.6 for advanced tasks without needing to alter your main configuration.

Question 4

How do I invoke Ccglm's GLM-4.6 capabilities within Claude Code?

Accepted Answer

You can use the `mcp__ccglm-mcp__glm_route` tool directly with a prompt, or, if configured, use a simple hashtag like `#ccglm` followed by your query (e.g., `#ccglm Generate an API REST in Python`) directly within your Claude Code interface.

Question 5

Can Ccglm perform in-depth analysis of complex codebases?

Accepted Answer

Absolutely. Ccglm is built for deep code analysis, featuring configurable extended timeouts of up to 40 minutes to handle complex problems. It also intelligently excludes internal files (like `.claude/` or `.git/`) from tracking for more focused and relevant analysis.

Ccglm

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