aggregate
AI agents invoke aggregate to trigger actions in MCP Database 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.
Aggregation pipelines in MongoDB can execute complex data processing operations, including stages like $merge or $out that write results to collections, or $lookup for cross-collection reads.
From the tool's definition Tool name is 'aggregate'; server description mentions 'running aggregation pipelines' as a supported operation. Description is empty, so classification is inferred from context.
Attacks that exploit this kind of access
aggregate. It is categorised as a Execute tool in the MCP Database Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP Database Server MCP server in PolicyLayer and add a rule for aggregate: 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 MCP Database Server. Nothing to install.
aggregate 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 aggregate 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 aggregate. 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.
aggregate is provided by the MCP Database Server MCP server (manpreet2000/mcp-database-server). 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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