GLM Subagent MCP
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Alternatives to GLM Subagent MCP
- AlicenseAqualityCmaintenanceEnables Claude to consult GLM-4.6's architectural intelligence for system design, code analysis, scalability patterns, and technical decision-making. Provides specialized tools for enterprise architecture consultation, distributed systems design, and code review through the Model Context Protocol.515MIT
- AlicenseAqualityCmaintenanceRun DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.231MIT
- AlicenseAqualityDmaintenanceA Model Context Protocol server that routes tasks to Z.ai's GLM-4.7 model, enabling Claude Code to delegate work to a more cost-efficient AI model without sacrificing quality.132MIT
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- AlicenseAqualityAmaintenanceExposes Z.ai GLM models (GLM-5.3 and siblings) as callable tools within Claude Code and Claude Desktop, enabling large-context second opinions, bulk grunt work, and independent model reasoning mid-conversation.3264 npmMIT
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- AlicenseNot gradedqualityCmaintenanceEnables Claude Code to delegate tasks to Google Antigravity (Gemini) as an autonomous subagent, including codebase exploration, architecture analysis, multi-file code generation, and technical Q&A, without requiring external API keys.MIT
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: glm_agent performs full repo work with file access, glm_delegate handles text-only subtasks, glm_recommend advises on model choice, and glm_status shows usage and config. There is no overlap or ambiguity.
All tool names follow a consistent 'glm_' prefix followed by a descriptive word (agent, delegate, recommend, status). The pattern is uniform with lowercase and underscores, making it easy to understand each tool's function.
With 4 tools, the set is well-scoped for the server's purpose of providing GLM subagent capabilities. Each tool justifies its existence, covering distinct modes of interaction without unnecessary bloat or deficiency.
The tool surface covers the full lifecycle: doing work (agent and delegate), getting advice on which to use (recommend), and monitoring usage (status). There are no obvious gaps for the intended use case of a GLM subagent.