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ToolProduction ReadyMCP
mate
by antiv
Production multi-agent orchestration with MCP, persistent memory, and dashboard
Python
Updated Jul 25, 2026
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Overview
Orchestrates production multi-agent workflows with database-driven configs and a web dashboardlink. Uses Google ADK and MCP for agent-to-agent messaging for agent-to-agent messaging, supports 50+ LLM providers, persistent memory, and RBAC for governance. Includes a FastAPI dashboard for monitoring and long-lived agent track records.
Key Benefits
As agents become more autonomous, tracking who did what and why is essential for trust and accountability. Mate builds operational primitives — persistence, RBAC, dashboarding, and MCP messaging — so teams can record agent interactions and evaluate agent track records over time. That visibility makes continuous agent evaluation and governance practical in production systems.
Best For
Engineering teams deploying multi-agent systems that need production-grade orchestration, governance, and persistent agent audits.
Applications
- Orchestrating long-running multi-agent workflows with persistent memory and RBAC
- Recording and auditing agent interactions to build agent track records for governance
- Connecting multiple LLM providers (50+) under a single MCP-based orchestration layer
- Monitoring agent behavior via a FastAPI dashboard for production observability
Works With
google-adklitellmollamafastapipython
Topics
agent-orchestrationai-agentsdashboardfastapigoogle-adklitellmllmmcpmulti-agentollama+2 more
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Keywords
multi-agent trustagent-to-agent evaluationagent track recordmulti-agent orchestration