AI agents call tenets_session to retrieve information from Tenets without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Given the server's role in code context aggregation and prompt injection of principles, this tool likely retrieves or queries session state/data without modifying it. The naming pattern matches other tools on the server (tenets_get_tool_schema, tenets_examine, tenets_search_tools) that appear to be Read operations. However, with an empty description, confidence is moderate.
From the tool's definition Tool name 'tenets_session' suggests session retrieval or query operations consistent with the server's context aggregation purpose. Description is empty, limiting direct evidence.
Documented attack patterns abuse exactly the kind of access tenets_session gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Tenets, and nothing reaches the server without passing your rules. This is the rule we recommend for tenets_session:
{
"version": "1",
"default": "deny",
"tools": {
"tenets_session": {}
}
}tenets_session is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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tenets_session. It is categorised as a Read tool in the Tenets MCP Server, which means it retrieves data without modifying state.
Register the Tenets MCP server in PolicyLayer and add a rule for tenets_session: 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 Tenets. Nothing to install.
tenets_session 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 tenets_session 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 tenets_session. 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.
tenets_session is provided by the Tenets MCP server (jddunn/tenets). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Tenets, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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10 Tenets tools catalogued and risk-classified — across an index of 43,000+ MCP servers.