glm-mcp 0.4.0

MCP server for ZhipuAI GLM — chat and text embeddings

glm-mcp

MCP server for ZhipuAI GLM — exposes chat and text embeddings to Claude Code (and any MCP-compatible client) via the OpenAI-compatible API.

Tools

Tool	Description
glm_chat	Text completion — default model glm-4-flash, pass model= to use any GLM chat model (e.g. glm-5). Supports single-turn and multi-turn (messages= parameter).
glm_embed	Text embeddings — default model embedding-3, pass model= to override
glm_usage_summary	Query token usage from ~/.glm-mcp/usage.jsonl. Parameters: days (default 7), model (optional filter). Returns period, total tokens, by_tool, by_model.

Quick Start

Install via uvx (recommended)

uvx glm-mcp

Add to Claude Code

Add to ~/.claude.json:

{
  "mcpServers": {
    "glm-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": ["glm-mcp"],
      "env": {
        "GLM_API_KEY": "your_api_key_here"
      }
    }
  }
}

Get your API key at https://open.bigmodel.cn/.

Run from source

git clone https://github.com/sky-zhang01/glm-mcp
cd glm-mcp
uv sync
GLM_API_KEY=your_key uv run glm-mcp

Environment Variables

Variable	Required	Default	Description
GLM_API_KEY	Yes	—	ZhipuAI API key
GLM_BASE_URL	No	https://open.bigmodel.cn/api/paas/v4/	API endpoint override
GLM_MCP_LOG_DIR	No	~/.glm-mcp/	Directory for usage.jsonl token log

Token Usage Logging

Each tool call appends a JSON line to ~/.glm-mcp/usage.jsonl:

{"timestamp": "...", "tool": "glm_chat", "model": "glm-4-flash", "input_tokens": 13, "output_tokens": 15}

Development

uv sync --dev
uv run pytest --cov=glm_mcp --cov-report=term-missing

License

MIT