Modifying operations that overwrite data. Supported operations: edit_element, upgrade_element Element types: persona, skill, template, agent, memory, ensemble These operations modify existing data, potentially overwriting previous values. Note: Memories are append-only and do not support edit...
Part of the DollhouseMCP MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use mcp_aql_update to create or modify resources in DollhouseMCP. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call mcp_aql_update repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach DollhouseMCP.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
mcp_aql_update:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full DollhouseMCP policy for all 5 tools.
Agents calling write-class tools like mcp_aql_update have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
Modifying operations that overwrite data. Supported operations: edit_element, upgrade_element Element types: persona, skill, template, agent, memory, ensemble These operations modify existing data, potentially overwriting previous values. Note: Memories are append-only and do not support edit_element. Use addEntry (CREATE) to add new entries. Quick start example: { operation: "edit_element", element_type: "persona", params: { element_name: "MyPersona", input: { description: "Updated description" } } } { operation: "edit_element", element_type: "persona", params: { element_name: "Friendly-Teacher", input: { instructions: "Updated behavioral directives." } } } { operation: "edit_element", element_type: "agent", params: { element_name: "code-reviewer", input: { instructions: "Updated agent behavioral profile.", goal: { template: "Complete: {task}" } } } } { operation: "upgrade_element", element_type: "agent", params: { element_name: "task-planner" } } Discover required parameters — use mcp_aql_read: { operation: "introspect", params: { query: "operations", name: "edit_element" } }. It is categorised as a Write tool in the DollhouseMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Add a rule in your Intercept YAML policy under the tools section for mcp_aql_update. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the DollhouseMCP MCP server.
mcp_aql_update is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the mcp_aql_update rule in your Intercept 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 Intercept policy for mcp_aql_update. 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.
mcp_aql_update is provided by the DollhouseMCP MCP server (@dollhousemcp/mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept