OpenCode Helper MCP
Related Servers
Alternatives to OpenCode Helper MCP
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceEnables Claude Code to delegate bounded, read-only analysis and isolated patch proposals to the locally installed Codex CLI over MCP, with sanitized live status, revision-aware polling, and reviewable results.1MIT
- AlicenseAqualityCmaintenanceEnables Codex to delegate coding tasks to an OpenCode CLI locally, returning structured results such as exit codes, session summaries, tool calls, and git diffs.2MIT
- FlicenseNot gradedqualityCmaintenanceEnables MCP clients like Claude Code to delegate coding tasks to a local model through a configurable coding-agent CLI backed by any OpenAI-compatible endpoint, with tools for health checks, task execution, and context-aware file modifications.-
- AlicenseAqualityCmaintenanceAnalyzes a local codebase and exposes its structure, per-file summaries, dependency graph, and complexity hotspots as tools for MCP clients like Claude.4MIT
- FlicenseAqualityCmaintenanceBridges Codex to external CLI coding agents for read-only code analysis and deterministic quality fixes.9-
- AlicenseNot gradedqualityBmaintenanceLets Claude Code delegate tasks to the OpenCode CLI, choosing cost-effective models by intelligence tier and tracking usage.18,358 npmMIT
TDQS
Scored across 3 tools
The three tools share the same core operation—analyzing code at low reasoning effort—and differ only by backend model. Their descriptions include model names and a fallback order, but there is no distinct purpose-based choice; an agent can only distinguish them by which fallback step it happens to need.
All tools follow the consistent pattern analyze_code_<model>, with matchings-style and no mixing of verbs or argument formats. The naming is predictable and readable.
Three tools is not necessarily bloated, and the fallback approach justifies multiple endpooints. However, this functionality could just as easily be a single tool with model parameter, so the count is slightly inflated by the redundancy.
The server covers its narrow read-only code analysis goal by providing three fallback models. But beyond analyzing a snippet/no input, there is no capability for fetching code, changing analysis params, handling analysis output, or performing any related helper task, which leaves the surface limited.