Skill: conanwhf/glm-mcp-server-use (version 1.0.2)

--- name: glm-mcp-server-use description: GLM MCP Server Use for OpenClaw. Configure and use the 4 official Z.AI / GLM MCP servers (vision, web search, web reader, zread) with environment-variable API-key auth. Use for endpoint wiring, schema inspection, smoke tests, and troubleshooting MCP calls. --- # GLM MCP Server Use ## Overview This skill provides a practical workflow to install, validate, and use the 4 official GLM MCP servers in OpenClaw: 1. Vision MCP (local stdio via `@z_ai/mcp-server`) 2. Web Search MCP (remote HTTP) 3. Web Reader MCP (remote HTTP) 4. Zread MCP (remote HTTP) It also includes scripts to read API key from environment variables, generate `mcporter` config, and run a smoke test. ## Quick Start From this skill directory: ```bash export Z_AI_API_KEY="your_zai_api_key" python3 scripts/setup_glm_mcp_servers.py --config ./tmp/mcporter-glm.json python3 scripts/smoke_test_glm_mcp.py --config ./tmp/mcporter-glm.json ``` Smoke test report will be written to `./tmp/glm-mcp-smoke-report.json`. ## API Key Resolution `setup_glm_mcp_servers.py` resolves API key from environment variables in this order: 1. `Z_AI_API_KEY` 2. `ZAI_API_KEY` 3. `GLM_API_KEY` 4. `ZHIPU_API_KEY` You can check key availability without exposing full token: ```bash python3 scripts/get_zai_api_key.py --masked ``` ## Installed MCP Entries The setup script writes these mcporter servers: - `web-search-prime` → `https://api.z.ai/api/mcp/web_search_prime/mcp` - `web-reader` → `https://api.z.ai/api/mcp/web_reader/mcp` - `zread` → `https://api.z.ai/api/mcp/zread/mcp` - `zai-vision` → stdio `npx -y @z_ai/mcp-server` (with `Z_AI_API_KEY`, `Z_AI_MODE=ZAI`) ## Validation Workflow ### 1) Inspect real schemas first ```bash mcporter --config ./tmp/mcporter-glm.json list web-reader --schema --json mcporter --config ./tmp/mcporter-glm.json list web-search-prime --schema --json mcporter --config ./tmp/mcporter-glm.json list zread --schema --json mcporter --config ./tmp/mcporter-glm.json list zai-vision --schema --json ``` ### 2) Minimal call examples ```bash mcporter --config ./tmp/mcporter-glm.json call web-search-prime.web_search_prime search_query="GLM-5.1 release notes" mcporter --config ./tmp/mcporter-glm.json call web-reader.webReader url="https://example.com" mcporter --config ./tmp/mcporter-glm.json call zread.get_repo_structure repo_name="microsoft/vscode" mcporter --config ./tmp/mcporter-glm.json call zai-vision.analyze_image image_source="/path/to/image.png" prompt="Describe key elements" ``` ## Important Runtime Notes - Actual tool names can differ from docs examples. Always trust `--schema` output from live server. - Search tool currently exposes `web_search_prime` and requires `search_query`. - Zread calls require `repo_name` (not `repo`). - Web Reader may return anti-bot or verification content for protected pages (for example some WeChat links). ## Troubleshooting - `Tool not found`: check exact tool name from `mcporter ... --schema --json`. - `parameter error`: verify argument names match schema exactly. - Empty/strange reader content: target page may block scraping or require interactive verification. - Vision local server issues: verify Node.js >= 22 and rerun with latest `@z_ai/mcp-server`. ## Resources - Server matrix and endpoint notes: `references/official-endpoints.md` - Tested behavior record: `references/test-report.md` - Scripts: `scripts/`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)