search_note_tool
AI agents call search_note_tool to retrieve information from Modular MCP Server with Python Tools without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Search operations are Read category—they query and retrieve data without side effects. Although the description is uninformative, the explicit 'search' verb in the name and the presence of note management tools on the server make it clear this retrieves note data. Severity is low because note searches have minimal blast radius; confidence is moderate (0.85) due to the missing description.
From the tool's definition Tool name 'search_note_tool' indicates a search operation on notes, which retrieves data without modifying it. The description is empty, but the name and sibling context (note_tool for management) strongly suggest a read-only query operation.
Attacks that exploit this kind of access
search_note_tool. It is categorised as a Read tool in the Modular MCP Server with Python Tools MCP Server, which means it retrieves data without modifying state.
Register the Modular MCP Server with Python Tools MCP server in PolicyLayer and add a rule for search_note_tool: 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 Modular MCP Server with Python Tools. Nothing to install.
search_note_tool is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the search_note_tool 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 search_note_tool. 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.
search_note_tool is provided by the Modular MCP Server with Python Tools MCP server (tunamsyar/ollama-mcp-py). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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