Read a single article by filename
AI agents call readArticle to retrieve information from Article Manager MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a query operation that retrieves article content based on a filename parameter. It has no side effects—it does not create, modify, delete, or execute code. The operation is purely informational.
From the tool's definition Tool name is 'readArticle' and description explicitly states 'Read a single article by filename'. It retrieves data without modification.
Attacks that exploit this kind of access
Read a single article by filename. It is categorised as a Read tool in the Article Manager MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Article Manager MCP Server MCP server in PolicyLayer and add a rule for readArticle: 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 Article Manager MCP Server. Nothing to install.
readArticle 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 readArticle 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 readArticle. 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.
readArticle is provided by the Article Manager MCP Server MCP server (joelmnz/mcp-markdown-manager). 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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