mcpField
O

ollama-handoff

Local
github.com/Michael-WhiteCapDataAI & Agents
Repository

About ollama-handoff

Offload cheap work from your AI agent to a local Ollama model, at zero cloud cost

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "michael-whitecapdata-ollama-handoff": {
      "command": "uvx",
      "args": [
        "ollama-handoff"
      ],
      "env": {
        "OLLAMA_URL": "<OLLAMA_URL>",
        "OLLAMA_DEFAULT_MODEL": "<OLLAMA_DEFAULT_MODEL>",
        "OLLAMA_NUM_CTX": "<OLLAMA_NUM_CTX>",
        "OLLAMA_KEEP_ALIVE": "<OLLAMA_KEEP_ALIVE>",
        "OLLAMA_TIMEOUT_S": "<OLLAMA_TIMEOUT_S>"
      }
    }
  }
}
Run commanduvx ollama-handoff
Environment variables to set
OLLAMA_URLBase URL of the Ollama server.
OLLAMA_DEFAULT_MODELDefault model used for handoffs.
OLLAMA_NUM_CTXContext window in tokens.
OLLAMA_KEEP_ALIVEHow long to keep the model resident in VRAM.
OLLAMA_TIMEOUT_SPer-request timeout in seconds.

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypiollama-handoff0.1.2

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

The maintainer has not added details yet. Check the README in the repository.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.