MCP Engineering Agent
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Engineering AgentShow the audit log for today's authorization decisions."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Engineering Agent
A security-first engineering agent demonstrating an MCP-style JSON-RPC tool boundary. It separates model orchestration from typed tools, authorization, and audit events.
Architecture
User -> Agent -> JSON-RPC/MCP Boundary -> Tool Registry -> Authorization -> Tool
`-> Audit EventRelated MCP server: enterprise-agent-lab
What this demonstrates
tools/listandtools/callJSON-RPC methodsTyped tool registration and discovery
Role-based authorization before tool execution
Read-only vs write-capable tool separation
UTC audit events for every authorization decision
Framework-light design that is easy to extend to a full MCP server
Why it matters
Agentic systems become risky when an LLM can directly execute arbitrary actions. This project treats tools as a privileged interface with explicit schemas and authorization boundaries.
Run
pip install -e '.[dev]'
python -m app.server
pytest -qNo real credentials or external systems are required for the demo.
This server cannot be deployed
Maintenance
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- AlicenseNot gradedqualityBmaintenanceEnables agent clients to safely connect to tools and execution resources through MCP with authorization, approvals, audit, chat-context isolation, SSH/Docker access, and long-running command session tracking.MIT
- AlicenseAqualityCmaintenanceProvides a security governance layer for AI agents to safely access upstream MCP servers, enforcing tool-level RBAC, parameter constraints, authentication via static tokens or OIDC, and tamper-evident audit logging.21Apache 2.0