Returns the leader schedule for an epoch.
AI agents call get_leader_schedule to retrieve information from Model Context Protocol Server for Solana Client without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Even though get_leader_schedule only reads data, uncontrolled read access leaks sensitive information and racks up API costs — an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
Returns the leader schedule for an epoch. It is categorised as a Read tool in the Model Context Protocol Server for Solana Client MCP Server, which means it retrieves data without modifying state.
Register the Model Context Protocol Server for Solana Client MCP server in PolicyLayer and add a rule for get_leader_schedule: 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 Model Context Protocol Server for Solana Client. Nothing to install.
get_leader_schedule 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_leader_schedule 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_leader_schedule. 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_leader_schedule is provided by the Model Context Protocol Server for Solana Client MCP server (tywenk/mcp-sol). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.