AI agents call read_file to retrieve information from Overleaf 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 file content from Overleaf without modifying, deleting, or executing anything. It is a straightforward read operation with minimal risk. The only potential concern would be if the file contained sensitive information, but that is a data sensitivity issue rather than a capability risk.
From the tool's definition Tool name is 'read_file' and description states 'Read a file from an Overleaf project'. The verb 'read' and absence of any modification language clearly indicate data retrieval with no side effects.
Documented attack patterns abuse exactly the kind of access read_file gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Overleaf MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for read_file:
{
"version": "1",
"default": "deny",
"tools": {
"read_file": {}
}
}read_file is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Read a file from an Overleaf project. It is categorised as a Read tool in the Overleaf MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Overleaf MCP Server MCP server in PolicyLayer and add a rule for read_file: 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 Overleaf MCP Server. Nothing to install.
read_file 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 read_file 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 read_file. 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.
read_file is provided by the Overleaf MCP Server MCP server (mjyoo2/overleafmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Overleaf MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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8 Overleaf MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.