search_all
AI agents call search_all to retrieve information from Pipedrive MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool name 'search_all' indicates a search/query operation typical of Read category. Sibling tools on the Pipedrive server are uniformly retrieval operations (get_*) with no side effects. The empty description lowers confidence slightly, but the naming convention and context strongly suggest this is a data retrieval tool. Severity is low as search operations have minimal blast radius when misused by an agent.
From the tool's definition Tool name 'search_all' with empty description; contextual pattern from sibling tools (get_activities, get_deal, get_deals, get_organizations, etc.) are all Read operations that retrieve CRM data without modification.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
search_all. It is categorised as a Read tool in the Pipedrive MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Pipedrive MCP Server MCP server in PolicyLayer and add a rule for search_all: 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 Pipedrive MCP Server. Nothing to install.
search_all 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_all 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_all. 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_all is provided by the Pipedrive MCP Server MCP server (osherai/pipedrive-mcp-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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