Retrieve top N chunks for given query
AI agents call retrieve to retrieve information from AI Research Assistant MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves document chunks from an indexed database based on a search query. It has no side effects—it does not create, modify, delete, or execute any operations. The blast radius of misuse is minimal; even an agent retrieving sensitive information from the knowledgebase would only expose data that already exists without altering state or triggering external actions. This is a straightforward Read operation.
From the tool's definition Tool name 'retrieve' and description 'Retrieve top N chunks for given query' indicate data retrieval without modification. The verb 'retrieve' and the context of a RAG (Retrieval-Augmented Generation) pipeline confirm this is a query/fetch operation.
Attacks that exploit this kind of access
Retrieve top N chunks for given query. It is categorised as a Read tool in the AI Research Assistant MCP Server MCP Server, which means it retrieves data without modifying state.
Register the AI Research Assistant MCP Server MCP server in PolicyLayer and add a rule for retrieve: 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 AI Research Assistant MCP Server. Nothing to install.
retrieve 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 retrieve 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 retrieve. 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.
retrieve is provided by the AI Research Assistant MCP Server MCP server (sagarkpoojary/sagar-mcp-project). 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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