bootstrap_agent_context
Restore continuity. On first run, also tell ChatGPT to guide the user through Polaris onboarding one question at a time.
This record as markdown: /tools/mapi-agent-memory/bootstrap-agent-context.md
What bootstrap_agent_context does on Mapi Agent Memory
AI agents invoke bootstrap_agent_context to trigger actions in Mapi Agent Memory. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why bootstrap_agent_context is rated High
bootstrap_agent_context triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs bootstrap_agent_context safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mapi Agent Memory, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For bootstrap_agent_context, this is the rule to start with:
bootstrap_agent_context stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mapi Agent Memory, apply this rule, and every bootstrap_agent_context call is checked against it from then on.
Questions about bootstrap_agent_context
Restore continuity. On first run, also tell ChatGPT to guide the user through Polaris onboarding one question at a time. It is categorised as a Execute tool in the Mapi Agent Memory MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mapi Agent Memory MCP server in PolicyLayer and add a rule for bootstrap_agent_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 Mapi Agent Memory. Nothing to install.
bootstrap_agent_context is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the bootstrap_agent_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 bootstrap_agent_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.
bootstrap_agent_context is provided by the Mapi Agent Memory MCP server (cabo0m/mapi-agent-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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