Return nodes carrying finding-style annotations.
AI agents call findings to retrieve information from Trailmark MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool only retrieves/returns nodes that have finding-style annotations — a pure read/query operation with no side effects. Severity is low because it only reads analysis data from the repository.
From the tool's definition Return nodes carrying finding-style annotations
Attacks that exploit this kind of access
Return nodes carrying finding-style annotations. It is categorised as a Read tool in the Trailmark MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Trailmark MCP Server MCP server in PolicyLayer and add a rule for findings: 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 Trailmark MCP Server. Nothing to install.
findings 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 findings 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 findings. 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.
findings is provided by the Trailmark MCP Server MCP server (parsiya/trailmark-mcp-server). 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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