glm-mcp
MCP server for ZhipuAI GLM — exposes chat, text embeddings, translation, vision, and OCR 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). Sampling: temperature=0.7, top_p=0.95 (pass top_p=None to omit). Auto-fallback on transient errors (429/503/timeout/connection) via auto_fallback=True (default). Use avoid_peak_hours=True to pre-emptively switch during peak hours (UTC+8 14:00–18:00). |
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. |
glm_translate |
Pure single-language translation — default model glm-4.7. Parameters: text, target_lang ("ja", "zh", "en"), source_lang (default "auto"), style ("formal" or "casual", default "formal"). Sampling: temperature=1.0, top_p=0.8 (GLM-4.7 Plan B: top_p as primary control; pass top_p=None to omit). Outputs ONLY the target language, solving the mixed Chinese–Japanese output problem common with general LLMs. |
glm_vision |
Multimodal image analysis — default model glm-4.6v. Parameters: image_url (HTTP/HTTPS URL or Base64 string), prompt, detail ("auto", "low", "high"), max_tokens (default 2048). Sampling: temperature=0.2, top_p=0.9 (focused stable analysis; pass top_p=None to omit). Auto-fallback to glm-4.6v-flash on 429/503/timeout. Bare Base64 strings are automatically prefixed with data:image/png;base64,. |
glm_ocr |
Document and image OCR — default model glm-ocr. Parameters: file (HTTP/HTTPS URL, Base64 string, data: URI, or local file path), model, start_page_id, end_page_id. Returns extracted text as Markdown. Local files are auto-encoded as Base64; bare Base64 strings are prefixed with data:application/pdf;base64,. |
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, "fallback_used": false, "original_model": null, "fallback_reason": null}
When fallback is triggered:
{"timestamp": "...", "tool": "glm_chat", "model": "glm-4.7", "input_tokens": 13, "output_tokens": 15, "fallback_used": true, "original_model": "GLM-5", "fallback_reason": "429"}
Development
uv sync --dev
uv run pytest --cov=glm_mcp --cov-report=term-missing
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for glm-mcp 0.8.1
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