AI agents call list_contexts to retrieve information from FastMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves context data using filters but does not create, modify, delete, or execute external operations. It is a read-only data retrieval function with minimal risk.
From the tool's definition Tool name 'list_contexts' and description 'List all contexts with optional filtering by model name or tag' indicates a retrieval operation with no modification, deletion, or side effects.
Attacks that exploit this kind of access
List all contexts with optional filtering by model name or tag. It is categorised as a Read tool in the FastMCP MCP Server, which means it retrieves data without modifying state.
Register the Fast MCP server in PolicyLayer and add a rule for list_contexts: 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 FastMCP. Nothing to install.
list_contexts 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 list_contexts 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 list_contexts. 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.
list_contexts is provided by the Fast MCP server (ryuichi1208/datadog-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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