I’ve been working on AgentxSuite, an open source control plane for AI agents built around the Model Context Protocol (MCP).
Most teams building agent features run into the same issues:
each agent needs its own tool wiring
permissions, policies and audit logs scatter across different services
no central place to register tools, resources or prompts
hard to track what an agent actually did across runs
integrating with external MCP servers (Postgres, filesystem, etc.) is repetitive
AgentxSuite tries to solve this by giving you a single layer to manage:
agents
tools
resources
prompts
policies
audit trails
token and usage tracking
multiple MCP servers (local or remote)
It also includes an Agent Designer Canvas to visually inspect the full graph of agents, their tools and their policies.
If you want to integrate MCP into your own product, or if you’re exploring multi-agent architectures with proper access control, feedback welcome.
https://github.com/alparn/agentxsuite
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AgentxSuite – Open-Source Control Plane for AI Agents Using MCP · HackerTrans
Most teams building agent features run into the same issues:
each agent needs its own tool wiring
permissions, policies and audit logs scatter across different services
no central place to register tools, resources or prompts
hard to track what an agent actually did across runs
integrating with external MCP servers (Postgres, filesystem, etc.) is repetitive
AgentxSuite tries to solve this by giving you a single layer to manage:
agents
tools
resources
prompts
policies
audit trails
token and usage tracking
multiple MCP servers (local or remote)
It also includes an Agent Designer Canvas to visually inspect the full graph of agents, their tools and their policies.
If you want to integrate MCP into your own product, or if you’re exploring multi-agent architectures with proper access control, feedback welcome. https://github.com/alparn/agentxsuite