Project NOVA MCP Server

Project NOVA is a multi‑agent AI orchestration platform that tackles the common pain point of scattered expertise across an organization. In many environments developers, data scientists, and domain specialists rely on a patchwork of tools—knowledge bases, digital audio workstations (DAWs), home‑automation hubs, and custom APIs. Managing these disparate systems through a single conversational interface is cumbersome; each tool requires its own authentication, data schema, and interaction logic. NOVA solves this by exposing a unified Model Context Protocol (MCP) server that routes user intents to the most appropriate agent, each of which is a domain‑specific expert. The result is a seamless, conversational experience where an AI assistant can answer complex queries, trigger workflows, or manipulate external applications without the user needing to switch contexts.

At its core, NOVA comprises three tightly coupled layers. First, agents encapsulate specialized knowledge and operational logic for a particular domain—whether that’s querying a corporate wiki, controlling smart lights, or adjusting DAW parameters. Second, the n8n workflow engine orchestrates these agents, handling stateful interactions, error recovery, and conditional branching. Finally, the MCP server acts as the communication bridge between an external AI client (e.g., Claude, GPT‑4) and the internal agents. By adhering to MCP’s resource, tool, prompt, and sampling contracts, NOVA guarantees that the AI can discover available capabilities dynamically, request context‑aware prompts, and receive structured responses in a predictable format.

Key capabilities of NOVA include:

• Dynamic Agent Discovery: The MCP server publishes a catalog of agents and their associated tools, allowing the AI to query which experts are available for a given task.
• Contextual Prompt Injection: Each agent can provide tailored system prompts that shape the AI’s behavior, ensuring consistent responses aligned with domain best practices.
• Workflow‑Driven Execution: Complex tasks that span multiple agents are encoded as n8n workflows, enabling the AI to trigger multi‑step processes—such as pulling data from a knowledge base, formatting it for a DAW plugin, and executing a rendering job—without manual intervention.
• Secure API Integration: Agents can encapsulate credentials and token management, so the AI never exposes sensitive information while still interacting with protected services.

Real‑world scenarios that benefit from NOVA include:

• Knowledge Management: A developer asks the AI to retrieve a design document from an internal wiki and summarize it for a sprint meeting; NOVA routes the request to the knowledge‑base agent, which fetches and formats the content before returning it.
• Home Automation: A user instructs the AI to “dim the living room lights at sunset”; the home‑automation agent translates this into API calls to the lighting system via n8n, handling timing and device selection automatically.
• Music Production: A producer requests the AI to “apply a vintage chorus effect to track 3”; NOVA invokes the DAW agent, which sends the appropriate plugin commands and confirms completion.

For developers integrating AI assistants into their tooling stack, NOVA offers a plug‑and‑play MCP server that abstracts away the complexity of multi‑agent coordination. By exposing a single endpoint for discovery and execution, it enables rapid prototyping of conversational workflows while maintaining strict separation of concerns between domain logic and AI orchestration. This combination of modular agents, workflow automation, and MCP compliance gives NOVA a distinct advantage for teams looking to embed intelligent assistants into heterogeneous environments.