Export the game history as structured data for reconstruction into a narrative book. Use get_chapter_for_export to fetch individual chapters for writing.
AI agents call export_story to retrieve information from DMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool reads and exports existing game history/story data without modifying any state. It retrieves structured data for narrative reconstruction, which is a pure read operation with no side effects.
From the tool's definition Export the game history as structured data for reconstruction into a narrative book. Use get_chapter_for_export to fetch individual chapters for writing.
Documented attack patterns abuse exactly the kind of access export_story gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and DMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for export_story:
{
"version": "1",
"default": "deny",
"tools": {
"export_story": {}
}
}export_story is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Export the game history as structured data for reconstruction into a narrative book. Use get_chapter_for_export to fetch individual chapters for writing. It is categorised as a Read tool in the DMCP MCP Server, which means it retrieves data without modifying state.
Register the D MCP server in PolicyLayer and add a rule for export_story: 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 DMCP. Nothing to install.
export_story 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 export_story 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 export_story. 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.
export_story is provided by the D MCP server (shawnrushefsky/dmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from DMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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204 DMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.