get_decision_graph
Read the decision GRAPH around one decision: the decisions it relates to and those that relate to it, each edge typed (supersedes | amends | refines | depends_on | conflicts_with | relates_to) with its reason. refines edges are the sub-decisions: a big ruling broken into the smaller calls that im...
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What get_decision_graph does on Adrata
AI agents call get_decision_graph to retrieve information from Adrata without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why get_decision_graph is rated Low
Even though get_decision_graph 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 get_decision_graph safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Adrata, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_decision_graph, this is the rule to start with:
get_decision_graph 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 Adrata, apply this rule, and every get_decision_graph call is checked against it from then on.
Questions about get_decision_graph
Read the decision GRAPH around one decision: the decisions it relates to and those that relate to it, each edge typed (supersedes | amends | refines | depends_on | conflicts_with | relates_to) with its reason. refines edges are the sub-decisions: a big ruling broken into the smaller calls that implement it. conflicts_with edges are two live rulings the owner has not picked between — read those before acting on either. Use this to walk a decision chain instead of paging through list_decisions. It is categorised as a Read tool in the Adrata MCP Server, which means it retrieves data without modifying state.
Register the Adrata MCP server in PolicyLayer and add a rule for get_decision_graph: 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 Adrata. Nothing to install.
get_decision_graph 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 get_decision_graph 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 get_decision_graph. 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.
get_decision_graph is provided by the Adrata MCP server (@adrata/adrata-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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