AgentGuard

About

AgentGuard addresses the critical 'false progress' problem in AI agent operations, where agents might report task completion without actual work being done. It acts as an MCP server that sits between users and their AI agents, enforcing accountability through predefined contracts. Users specify tasks and required evidence, which AgentGuard independently verifies, preventing blind trust in agent outputs and ensuring that 'no evidence' truly means 'not done'. Every state transition and verification is recorded in an append-only audit log, providing a complete and immutable record of agent activities.

Key Features

• Supports multi-agent connections to a single instance via HTTP Server-Sent Events (SSE) for real-time communication.
• Contract-based verification for single agents, defining tasks, evidence, and operational bounds.
• Orchestrates multi-agent pipelines as directed acyclic graphs (DAGs), allowing stages to run in dependency order with artifact passing.
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• Enables orchestrator agents to decompose high-level goals into sub-contracts for worker agents with enforced limits on depth, sub-contracts, and cost.
• Maintains an append-only audit log, recording every state transition and verification for compliance and debugging.

Use Cases

• Ensure deployment tasks by AI agents are independently verified with live checks, preventing false reports of completion.
• Orchestrate complex multi-step AI agent pipelines (e.g., code generation, testing, deployment) with dependencies and artifact passing.
• Enable high-level orchestrator agents to delegate and manage sub-tasks to worker agents with built-in accountability and constraint enforcement.