Pull a model from the Ollama registry. Downloads the model to make it available locally.
AI agents use ollama_pull to create or update resources in Ollama MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ollama MCP Server environment.
This tool downloads a model from an external registry and stores it locally, which is a write operation (creating new data on the local system). It is reversible (the model can be deleted afterwards). The blast radius is medium since it could consume significant disk space or introduce an untrusted model, but it does not execute code or irreversibly destroy data.
From the tool's definition Pull a model from the Ollama registry. Downloads the model to make it available locally.
Documented attack patterns abuse exactly the kind of access ollama_pull gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ollama MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for ollama_pull:
{
"version": "1",
"default": "deny",
"tools": {
"ollama_pull": {
"limits": [
{
"counter": "ollama_pull_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}ollama_pull stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Pull a model from the Ollama registry. Downloads the model to make it available locally. It is categorised as a Write tool in the Ollama MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ollama MCP Server MCP server in PolicyLayer and add a rule for ollama_pull: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ollama MCP Server. Nothing to install.
ollama_pull is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the ollama_pull rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for ollama_pull. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
ollama_pull is provided by the Ollama MCP Server MCP server (rawveg/ollama-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 13 Ollama MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
13 Ollama MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.