Ollama Handoff runs on your own machine — the client starts it, so there is no endpoint to ping. 68 installs a week from pypi.
Offload cheap work from your AI agent to a local Ollama model, at zero cloud cost.
The linked repository no longer exists on GitHub — it was deleted or made private.
We have not read this server's code yet, 20 d ago · rules ccca72095570
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
этот файл ставится пользователю, но в репозитории его нет
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We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add ollama-handoff -- uvx ollama-handoff
{
"mcpServers": {
"ollama-handoff": {
"command": "uvx",
"args": [
"ollama-handoff"
]
}
}
}
[mcp_servers.ollama-handoff]
command = "uvx"
args = ["ollama-handoff"]
{
"mcpServers": {
"ollama-handoff": {
"command": "uvx",
"args": [
"ollama-handoff"
]
}
}
}
{
"servers": {
"ollama-handoff": {
"type": "stdio",
"command": "uvx",
"args": [
"ollama-handoff"
]
}
}
}
Optional settings from the registry entry, left out of the block above:
OLLAMA_URL (Base URL of the Ollama server), OLLAMA_DEFAULT_MODEL (Default model used for handoffs), OLLAMA_NUM_CTX (Context window in tokens), OLLAMA_KEEP_ALIVE (How long to keep the model resident in VRAM), OLLAMA_TIMEOUT_S (Per-request timeout in seconds).
Offload grunt work from your premium agent to cheap models — auto-routing and billing isolation.
Let a planning agent hand bounded language work to a local Ollama model.
Fan a goal out to cheap parallel LLM workers on your own key or a free local Ollama. Keep your mind.
Connect Claude to any OpenAI-compatible LLM endpoint and offload routine work to a local model.
Deploy localhost to a private, authenticated link from your AI coding agent.
Local Work Model MCP server for agent work that learns from real outcomes.
Local, payload-free AI cost visibility for agents. Query spend by model, route, or tagged work.
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Answers built from our own checks of this server.