load_party
Store the party the AI will play, as the JSON array of characters exported from the betaOSRIC builder (the value under localStorage key
This record as markdown: /tools/torch-to-crown/load-party.md
What load_party does on Torch-to-Crown
AI agents call load_party to retrieve information from Torch-to-Crown without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why load_party is rated Low
Even though load_party only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs load_party safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Torch-to-Crown, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For load_party, this is the rule to start with:
load_party is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Torch-to-Crown, apply this rule, and every load_party call is checked against it from then on.
Questions about load_party
Store the party the AI will play, as the JSON array of characters exported from the betaOSRIC builder (the value under localStorage key. It is categorised as a Read tool in the Torch-to-Crown MCP Server, which means it retrieves data without modifying state.
Register the Torch-to-Crown MCP server in PolicyLayer and add a rule for load_party: 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 Torch-to-Crown. Nothing to install.
load_party 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 load_party 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 load_party. 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.
load_party is provided by the Torch-to-Crown MCP server (Diogenes187/Torch-to-Crown). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Torch-to-Crown, and thousands of servers like it.
This server
Across the catalogue