local-delegate
Related Servers
Alternatives to local-delegate
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceMCP server connecting Claude Code to LM Studio, delegating token-expensive tasks to a local model while keeping the cloud model in control. It reduces cloud context usage by reading files locally and returning only the processed results.4MIT
- AlicenseNot gradedqualityDmaintenanceEnables Claude Code to delegate mechanical tasks (summaries, boilerplate, reformatting) to local models running in LM Studio.1MIT
- AlicenseNot gradedqualityBmaintenanceMCP server that delegates mechanical tasks like summarization, classification, extraction, and drafting to a local Llama.cpp LLM, serving as a cost-optimization layer while Claude handles reasoning and quality control.MIT
- AlicenseBqualityCmaintenanceDelegates heavy, repetitive, and verifiable tasks like PDF extraction, code analysis, and log processing to a local LLM to reduce token consumption for frontier AI models, while keeping decision-making with the main AI.8MIT
- AlicenseNot gradedqualityAmaintenanceEnables Claude to offload noisy commands, large files, and web research to a local OpenAI-compatible LLM, receiving only concise cited answers instead of the raw material. It also optionally delegates writing a single file inside an isolated git worktree, retrying until a Claude-authored test passes.269 npm2MIT
- FlicenseNot gradedqualityCmaintenanceEnables orchestrating models to delegate reading and answering questions about local files to a local LLM, avoiding sending file contents through the orchestrator's context.-
TDQS
Scored across 11 tools
Most tools target a clearly distinct task (classify, extract, translate, explain_code, describe_image, commit_msg), and the descriptions carefully explain routing. The main overlaps are local_summarize vs local_lint_summary (both summarize) and local_delegate as an explicit catch-all that can duplicate several specific tools, though the escape-hatch framing mitigates this.
Every tool uses the uniform local_<verb> snake_case pattern, with matching argument names (text/path, max_words, focus) repeated across tools. No mixed conventions or casing inconsistencies.
11 tools sits comfortably in the well-scoped 3-15 range. Each covers a distinct local-model capability plus a generic delegate and a diagnostics tool, so none feels redundant or bolted on.
The surface covers the core local-delegation lifecycle well: read-only diagnostics, generic and specialized text tasks, code tasks, vision, and file-server-side reads with a fallback/error envelope. Minor gaps remain (e.g. embeddings/rerank or a generic non-file code generation path), but agents can work around them via local_delegate.