dugubuyan/agent-nexus

AgentNexus

A service-boundary-aware coordination architecture for heterogeneous LLM code agents.

"Service boundaries, not agent roles, are the appropriate primitive for coordinating LLM agents in real software development."

Overview

Existing multi-agent frameworks (ChatDev, MetaGPT) organize agents around roles within a single simulated organization. AgentNexus takes a different approach: it coordinates agents at the service granularity, matching how real software systems are actually structured.

Each service registers as a sub-project, publishes versioned Markdown documents (requirements, design, API specs, config), and subscribes to documents from services it depends on. When a document changes, subscribers receive a diff-aware notification containing both the structured diff and the full latest content — enabling targeted, context-aware code modifications.

Key Features

• Versioned document store — SHA-256 dedup, full version history, per-service namespacing
• Publish-subscribe notifications — subscribe by exact doc ID or doc type
• Diff-aware updates — get_my_updates_with_context returns unified diff + full content in one call
• Lifecycle event hook — stage field marks the project's current lifecycle phase (design / development / testing / deployment / upgrade); transitions trigger milestone snapshots. Informational only — does not determine which documents a project needs (see v4-ideas §14)
• Service-Driven Agent Onboarding (SDAOP) — generate_instruction_file auto-generates IDE steering files (AGENTS.md, CLAUDE.md, Kiro steering, Cursor rules) for any connecting agent
• MCP HTTP server — streamable-HTTP transport, multiple agents connect simultaneously
• Out-of-band write endpoint — POST /api/documents accepts full content via HTTP body (zero LLM token cost)
• FTS5 full-text search — search_documents with BM25 ranking, phrase/prefix/boolean query support
• Planner AI layer — planner_chat, planner_plan, planner_overview MCP tools + configurable LLM backend
• Web Dashboard — browser-based UI to explore spaces, projects, and documents with full-text search
• AI Chat — built-in chat panel powered by Planner LLM for conversational document Q&A and service planning
• 281 tests — unit + property-based (Hypothesis)