rConfig MCP-AI
Code Meets Configuration
Tap into the Model Context Protocol to generate scripts, automate workflows, and explore configurations securely using your AI coding assistant.
AI for network reliability
Bridge the gap between human intent and machine execution with the power of the Model Context Protocol.
Configuration drift
AI-assisted detection and correction of unintended changes across your entire network fleet.
Automated scripts
Turn natural language into ready-to-run automation code for Python, Bash, or Ansible.
Open developer access
AI can browse, query, and act on rConfig’s open-source foundation via standardized MCP.
Private & secure
Absolutely no data leaves your environment. The MCP server runs locally within your infrastructure.
How MCP-AI works
Four stages — connect, engineer, explore, govern — each built to surface context without ever leaving the customer’s rConfig instance.
Connect your AI tools
Seamlessly integrate with Claude Code, Cursor, and ChatGPT. The MCP standard allows these models to automatically discover rConfig's capabilities without complex manual configuration.
- Native Claude & Cursor integration
- Automatic tool discovery via MCP
- Multi-model orchestration support
Intelligent engineering
Create backup scripts, diff API requests, and reporting pipelines in seconds. Just describe what you need, and watch the code appear, ready for review and secure execution.
- Precision script generation
- Real-time API diffing & testing
- Governed workflow automation
Explore rConfig’s core
Your AI assistant can securely browse models, documentation, and configuration metadata, giving it the specific context it needs to provide accurate, network-aware answers.
- Secure metadata indexing
- Deep configuration exploration
- Live documentation grounding
Enterprise governance
Benefit from full RBAC inheritance and strict separation between write-safe and read-safe operations. Every AI-driven action is logged for full audit compliance.
- Strict RBAC inheritance
- Read-safe execution environment
- Full audit logging for AI sessions
Model Context Protocol — Under the Hood
Exposed Toolset
rConfig exposes a curated “toolset” to AI models via MCP. These tools describe available API calls, schemas, and safe operations in a format LLMs natively understand.
- Describe API definitions & schemas
- Distinguish safe vs. unsafe operations
- Context-aware config inspection
All executed inside the customer’s rConfig instance. No external data egress.
The workflow
From prompt to production in five reviewable, audit-logged steps.
Natural-language request
Ask your AI assistant to perform a task.
Tool discovery
AI identifies available rConfig MCP tools.
Code generation
AI constructs the necessary API calls or scripts.
Review & run
You validate the logic, then execute securely.
Audit logged
Full traceability of the AI’s actions.
Who uses MCP-AI
Same underlying protocol, three different jobs — each team gets configuration-aware automation phrased for their workflow.
System integrators
Build and maintain complex automations faster. Generate boilerplate integration code for third-party tools instantly.
MSPs & DevOps
Generate multi-tenant onboarding scripts and compliance reports tailored to specific customer environments safely.
Automation engineers
Turn plain-language directives into Python, Bash, PowerShell, or PHP pipelines without manual syntax lookup.
Frequently Asked Questions
Bridge your AI with your Infrastructure
Deploy the rConfig MCP Server to give your AI assistants direct, governed access to your network data. Secure, scalable, and built for the enterprise.