MCP server for GLM chat completions using Zhipu AI models via AceDataCloud
A Model Context Protocol (MCP) server for Zhipu GLM chat completions via the AceDataCloud platform.
pip install mcp-glm
Set your AceDataCloud API token:
export ACEDATACLOUD_API_TOKEN=your_token_here
Get your token from https://platform.acedata.cloud.
mcp-glm
mcp-glm --transport http --port 8000
| Tool | Description |
|---|---|
glm_chat_completions | Run a GLM chat completion call |
glm_list_models | List available GLM models |
glm_get_usage_guide | Get the API usage guide |
MIT — see LICENSE.
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
uvx mcp-glmMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-acedatacloud-mcp-glm": {
"command": "uvx",
"args": [
"mcp-glm"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referencemcp-glmpypiio.github.AceDataCloud/mcp-glm works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.