GLM MCP Server Use

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.

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:

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:

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

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

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/