AI agents call list_tables to retrieve information from literateMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves structural information about the database (table names) with no side effects. It is a read-only operation that does not create, modify, delete, or execute any code. The low severity reflects that exposure of database schema is a minor information disclosure risk in an academic literature management context.
From the tool's definition Tool name 'list_tables' and description 'List all tables in the literature database' indicate a query operation that retrieves schema metadata without modifying or executing operations on data.
Documented attack patterns abuse exactly the kind of access list_tables gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and literateMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for list_tables:
{
"version": "1",
"default": "deny",
"tools": {
"list_tables": {}
}
}list_tables is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all tables in the literature database. It is categorised as a Read tool in the literateMCP MCP Server, which means it retrieves data without modifying state.
Register the literate MCP server in PolicyLayer and add a rule for list_tables: 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 literateMCP. Nothing to install.
list_tables 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 list_tables 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 list_tables. 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.
list_tables is provided by the literate MCP server (zongmin-yu/sqlite-literature-management-fastmcp-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from literateMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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15 literateMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.