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Delegate low-risk tasks to a cheaper model with main-agent review.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "cn-llm-mcp" yet — see the docs or source repo.
Use cn-llm-mcp to send this long document to a low-cost model for summarization. Return five key points and one risk note, then review and correct any obvious mistakes yourself.
A concise summary reviewed by the main agent, including key points and a confidence or risk note.
Through cn-llm-mcp, have a low-cost model generate a minimal patch based on this error and code. Then review it for side effects and provide the final recommendation.
A reviewable patch draft plus the main agent’s assessment of risks and suitability.
Use cn-llm-mcp to batch-process these low-risk tasks: clean up meeting notes, extract action items, and format the output consistently. Then consolidate the results and flag anything needing human confirmation.
A consolidated structured result with action items and flags for items needing further confirmation.
Delegate summarization, classification, extraction, and drafting tasks to a local LLM.
Offload non-critical LLM tasks to your own model to save premium quota.
Build, debug, and manage software tasks with natural language across LLMs.
Run Llama models locally for private, offline AI assistance.
Run local multi-model deliberation and synthesis on Mac for AI coding workflows.
Securely let AI read, search, and edit local files with local LLMs.