Get the current Decision OS context. Call this at the start of a task to understand: - Active case (if any) - Recent pressure events - Relevant foundations (from both project and global scopes) - Any conflicts between project and global foundations Returns the project name, active case details, a...
AI agents call get_context to retrieve information from Decision OS MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
get_context is a pure read operation that queries and returns data about the current state of the Decision OS system. It has no side effects, does not modify any data, and does not trigger external actions. The severity is low because even if misused, retrieving context information poses minimal risk—it is informational only.
From the tool's definition Tool description states it 'Get[s] the current Decision OS context' and 'Returns the project name, active case details, applicable foundations with source scope, and detected conflicts.' All operations are retrieval/query only with no modification, creation,…
Attacks that exploit this kind of access
Get the current Decision OS context. Call this at the start of a task to understand: - Active case (if any) - Recent pressure events - Relevant foundations (from both project and global scopes) - Any conflicts between project and global foundations Returns the project name, active case details, applicable foundations with source scope, and detected conflicts. It is categorised as a Read tool in the Decision OS MCP MCP Server, which means it retrieves data without modifying state.
Register the Decision OS MCP server in PolicyLayer and add a rule for get_context: 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 Decision OS MCP. Nothing to install.
get_context 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_context 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_context. 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_context is provided by the Decision OS MCP server (marianstefi20/decision-os-mcp). 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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