nexus-agents
Intelligent orchestration platform that routes tasks to the best AI model (Claude, Codex, Gemini, OpenCode) using LinUCB bandits, validates through consensus voting, and learns from outcomes. 29 MCP tools, dev pipeline, 8 memory backends.
Nexus Agents
The intelligence layer between you and your AI coding tools
Why Nexus Agents?
nexus-agents makes your AI coding tools work together intelligently. It coordinates Claude, Codex, Gemini, and OpenCode — routing each task to the best model using data-driven algorithms, validating outputs through multi-model consensus voting, and continuously improving through outcome-driven learning. Connect it to any MCP-compatible editor (Claude Code, Cursor, VS Code) and it handles the rest.
What it does for you:
- Routes intelligently — LinUCB bandit + TOPSIS scoring + adaptive bonuses pick the right model for each task, learned from real outcomes
- Enforces quality — consensus voting (7 algorithms including Bayesian higher-order), QA review loops, security scans with SARIF
- Learns over time — 8 memory backends track what works, feeding routing, planning, and research decisions
- Runs a full dev pipeline — research papers, plan architecture, vote on proposals, decompose into tasks, implement, QA review, ship
- Connects everything — 29 MCP tools, 9 research sources, graph workflows, checkpoint/resume, GitHub/GitLab issue tracking
You: "Review this code for security and performance"
↓
CompositeRouter selects best CLI per category → Security Expert + Code Expert
↓
Consensus-validated response — outcomes feed back into routing for next time
What it is NOT:
- Not an autonomous agent — humans stay in the loop via votes and harness mode
- Not a chat framework — it orchestrates real CLI tools with real file I/O
- Not a model API proxy — the intelligence IS the routing, quality gates, and learning
Architecture at a Glance
┌─────────────────────────────────┐
│ Your IDE / CLI │
│ (Claude Code, Cursor, VS Code) │
└──────────────┬──────────────────┘
│ MCP Protocol
┌──────────────▼──────────────────┐
│ nexus-agents server │
│ │
│ ┌──────────┐ ┌──────────────┐ │
│ │ 29 MCP │ │ Dev Pipeline │ │
│ │ Tools │ │ research→plan │ │
│ └────┬─────┘ │ →vote→impl │ │
│ │ │ →QA→ship │ │
│ ┌────▼─────┐ └──────────────┘ │
│ │Composite │ │
│ │Router │ ┌──────────────┐ │
│ │(9 stages)│ │ 8 Memory │ │
│ └────┬─────┘ │ Backends │ │
│ │ └──────────────┘ │
└───────┼─────────────────────────┘
┌────────────┼────────────┐
▼ ▼ ▼
┌────────┐ ┌────────┐ ┌──────────┐
│ Claude │ │ Gemini │ │ Codex │ ...
│ CLI │ │ CLI │ │ CLI │
└────────┘ └────────┘ └──────────┘
Quick Start (2 minutes)
1. Install
npm install -g nexus-agents
2. Verify
nexus-agents doctor
3. Use
With Claude Code (recommended):
nexus-agents setup # Auto-configures MCP server
Then in Claude: "orchestrate: Review this PR for issues"
Standalone CLI:
export ANTHROPIC_API_KEY=your-key
nexus-agents orchestrate "Explain the architecture of this codebase"
Security: In default MCP mode, the server communicates only via stdio with the parent process (no network exposure). The REST API (opt-in) auto-generates an API key on first start. For network-exposed deployments, set
NEXUS_AUTH_ENABLED=true. See SECURITY.md.
Capabilities
| Category | Details |
|---|---|
| Intelligent Routing | 9-stage CompositeRouter: budget-aware, LinUCB bandit, TOPSIS multi-criteria, preference-trained, weather-adaptive. Learns from outcomes. |
| Multi-Expert Orchestration | 9 built-in expert types (code, architecture, security, testing, docs, devops, research, PM, UX) coordinated by TechLead/Orchestrator agents |
| Consensus Voting | 7 algorithms: simple majority, supermajority, unanimous, weighted, ordered-weighted, higher-order Bayesian, incremental quorum |
| Development Pipeline | Research → Plan → Vote → Decompose → Implement → QA → Security. Three modes: autonomous, harness (caller implements), dry-run |
| Memory & Learning | 8 backends (session, belief, adaptive, routing, graph, hybrid, agentic, typed). Cross-session persistence. Outcomes feed routing. |
| Research System | 9 discovery sources (arXiv, GitHub, Semantic Scholar, etc). Auto-catalog, quality scoring, synthesis into topic clusters |
| Security | Sandboxing (Docker/policy), trust classification, SARIF parsing, input sanitization, red team pipeline, firewall |
| Graph Workflows | DAG-based workflow execution with checkpoint/resume, state reduction, and event hooks |
| 29 MCP Tools | Agent management, workflow execution, research, memory, codebase intelligence, repo analysis, consensus, operations |
Available Experts
| Expert | Specialization |
|---|---|
| Code | Implementation, debugging, optimization |
| Architecture | System design, patterns, scalability |
| Security | Vulnerability analysis, secure coding |
| Testing | Test strategies, coverage, test generation |
| Documentation | Technical writing, API docs |
| DevOps | CI/CD, deployment, infrastructure |
| Research | Literature review, state-of-the-art analysis |
| PM | Product management, requirements, priorities |
| UX | User experience, usability, accessibility |
| Infrastructure | Server management, bare metal, networking |
Supported CLIs & Providers
Nexus-agents routes tasks through 5 CLI adapters, each connecting to major AI providers:
| CLI | Provider | Best For |
|---|---|---|
| claude | Anthropic (Claude) | Complex reasoning, analysis |
| gemini | Google (Gemini) | Long context, multimodal |
| codex | OpenAI (Codex CLI) | Code generation, reasoning |
| codex-mcp | OpenAI (Codex MCP) | MCP-native Codex integration |
| opencode | Custom OpenAI-compat | Custom endpoints, local models |
CLI Commands
nexus-agents # Start MCP server (default)
nexus-agents doctor # Check installation health
nexus-agents setup # Configure Claude CLI integration
nexus-agents orchestrate "..." # Run task with experts
nexus-agents vote "proposal" # Multi-agent consensus voting
nexus-agents review <pr-url> # Review a GitHub PR
nexus-agents expert list # List available experts
nexus-agents workflow list # List workflow templates
nexus-agents config init # Generate config file
nexus-agents fitness-audit # Run fitness score audit
nexus-agents research query # Query research registry
nexus-agents --help # Full command list
See docs/ENTRYPOINTS.md for the complete CLI reference (28+ commands).
MCP Tools
When running as an MCP server, the following tools are available:
| Tool | Description |
|---|---|
orchestrate | Task orchestration with Orchestrator coordination |
create_expert | Create a specialized expert agent |
execute_expert | Execute a task using a created expert |
run_workflow | Execute a workflow template |
delegate_to_model | Route task to optimal model |
consensus_vote | Multi-model consensus voting on proposals |
list_experts | List available expert types |
list_workflows | List available workflow templates |
research_query | Query research registry (status, overlap, stats, search) |
research_add | Add paper to registry by arXiv ID |
research_discover | Discover papers/repos from external sources |
research_analyze | Analyze registry for gaps, trends, coverage |
research_catalog_review | Review auto-cataloged research references |
memory_query | Query across all memory backends |
memory_stats | Memory system statistics dashboard |
memory_write | Write to typed memory backends |
weather_report | Multi-CLI performance weather report |
issue_triage | Triage GitHub issues with trust classification |
run_graph_workflow | Execute graph-based workflows with checkpointing |
execute_spec | Execute AI software factory spec pipeline |
registry_import | Generate draft model registry entry |
query_trace | Query execution traces for observability |
repo_analyze | Analyze GitHub repository structure |
repo_security_plan | Generate security scanning pipeline for a repo |
research_add_source | Add non-paper source (GitHub repo, tool, blog) |
research_synthesize | Synthesize registry into topic clusters with themes |
extract_symbols | Extract code symbols from source files for analysis |
search_codebase | Search codebase for patterns, symbols, or text |
run_dev_pipeline | Full dev pipeline: research, plan, vote, implement, QA |
Configuration
Environment Variables:
| Variable | Description |
|---|---|
ANTHROPIC_API_KEY | Claude API key |
OPENAI_API_KEY | OpenAI API key |
GOOGLE_AI_API_KEY | Gemini API key |
NEXUS_LOG_LEVEL | Log level (debug/info/warn/error) |
Generate config file:
nexus-agents config init # Creates nexus-agents.yaml
Documentation
| Topic | Link |
|---|---|
| Full CLI Reference | docs/ENTRYPOINTS.md |
| Architecture | docs/architecture/README.md |
| Contributing | CONTRIBUTING.md |
| Coding Standards | CODING_STANDARDS.md |
| Quick Start Guide | QUICK_START.md |
Development
git clone https://github.com/williamzujkowski/nexus-agents.git
cd nexus-agents
pnpm install
pnpm build
pnpm test
Requirements: Node.js 22.x LTS, pnpm 9.x
Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feat/amazing-feature) - Commit with conventional commits (
feat(scope): add feature) - Open a Pull Request
See CONTRIBUTING.md for details.
License
MIT - See LICENSE
Built with Claude Code
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