AI agents invoke run to trigger actions in Ollama MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool triggers external operations (LLM inference execution) whose outcomes are dependent on the input arguments provided. While not destructive or financial, it represents the Execute category as it runs computational operations. The severity is high because a compromised agent could use this to perform arbitrary inferences, consume computational resources, or generate harmful outputs.
From the tool's definition Tool is named 'run' with description 'Run a model' in the context of Ollama MCP Server that manages local LLM execution. The sibling tools (cp, create, pull, push, rm, serve, show) indicate this server controls model lifecycle and execution.
Documented attack patterns abuse exactly the kind of access run 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 run:
{
"version": "1",
"default": "deny",
"tools": {
"run": {
"limits": [
{
"counter": "run_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Run a model. It is categorised as a Execute tool in the Ollama MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ollama MCP Server MCP server in PolicyLayer and add a rule for run: 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.
run is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run 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 run. 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.
run is provided by the Ollama MCP Server MCP server (nighttrek/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 10 Ollama MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
10 Ollama MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.