An MCP server that demonstrates sampling, enabling the server to request LLM completions from the client to assist in workflow tasks like planning work sessions.
Demonstrates how to implement sampling in MCP servers, allowing tools to request LLM content generation from the client without requiring external API integrations or credentials.
An MCP server that provides programmable spend limits and audit trails for AI agents to make payments from a dedicated wallet, preventing overspend and unauthorized transactions.
MCP server for priority-weighted token budget management in multi-agent LLM systems, enabling dynamic reallocation of unused tokens between agents based on priority and current spend.
An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.