[chuckadams]

Anyone know of a setup, perhaps with MCP, where I can get my local LLM to work in tandem on tasks, compress context, or otherwise act in concert with the cloud agent I'm using with Augment/Cursor/whatever? It seems silly that my shiny new M3 box just renders the UI while the cloud LLM alone refactors my codebase, I feel they could negotiate the tasks between themselves somehow.

[_joel]

There's a few Ollama-MCP bridge servers already (from a quick search, also interested myself):

ollama-mcp-bridge: A TypeScript implementation that "connects local LLMs (via Ollama) to Model Context Protocol (MCP) servers. This bridge allows open-source models to use the same tools and capabilities as Claude, enabling powerful local AI assistants"

simple-mcp-ollama-bridge: A more lightweight bridge connecting "Model Context Protocol (MCP) servers to OpenAI-compatible LLMs like Ollama"

rawveg/ollama-mcp: "An MCP server for Ollama that enables seamless integration between Ollama's local LLM models and MCP-compatible applications like Claude Desktop"

How you route would be an interesting challenge, presumably could just tell it to use the mcp for certain tasks, thereby offloading locally.

[rcarmo]

I've been toying with Visual Studio Code's MCP and agent support and gotten it to offload things like reference searches and targeted web crawling (look up module X on git repo Y via this URL pattern that the MCP server goes, fetches and parses).

I started by giving it a reference Python MCP server and asking it to modify the code to do that. Now I have 3-4 tools that give me reproducible results.

[101011]

This is the closest I've found that's akin to Claude Code: https://aider.chat/