n3rv

mcp
Guvenlik Denetimi
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  • network request — Outbound network request in .opencode/plugins/n3rv-lifecycle.js
  • process.env — Environment variable access in .opencode/tools/n3rv-stats.ts
  • network request — Outbound network request in .opencode/tools/n3rv-stats.ts
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Bu listing icin henuz AI raporu yok.

SUMMARY

Engineering infrastructure for opencode AI agents: memory, skills, subagent dispatch.

README.md
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  Because an angel without a harness is unmanageable.
  And a harness without an angel is just expensive metal.

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PyPI
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n3rv is an open-source engineering harness designed to contain, restrain, and orchestrate Large Language Models (LLMs). Instead of treating agents as independent chatbots, N3RV builds a rigid operational framework — handling tools, dual-store memory, and real-time project context injection. Integrates natively with opencode via MCP servers, agent skills, slash commands, and sub-agents.

ArchitectureSDD WorkflowMCP ToolsDeploymentEvangelionSecurityContributing


⚡ Core Architecture

The base model is the Angel: raw, uncontained, and unpredictable. N3RV is the restraint harness that binds it to your local development environment.

  • MAGI Consensus Architecture: Dual-layer memory routing utilizing ChromaDB for semantic long-term retrieval and SQLite for rigid ACID-compliant session state tracking (verdicts, relations).
  • LCL Project Injection: Automatic parsing of environment manifests (pyproject.toml, package.json). The agent "breathes" your project architecture from session one.
  • 14 Synchronized Agent Skills (The EVAs): Specialized skill files for distinct phases of the software development lifecycle — code, testing, commits, GitHub ops, git ops, SDD (explore → propose → spec → design → tasks → apply → verify → archive), judgment-day review.
  • 10 Sub-Agents: Dedicated agent configs for each SDD phase + git-ops + github-ops, isolated by responsibility.
  • MCP Protocol Integration: 5 native MCP servers — n3rv-memory (semantic + relational memory), n3rv-hub (A2A task delegation), GitHub wrapper, Context7 contextual search, sequential-thinking.

🚀 Synchronization Sequence

Initialize the harness inside your local repository:

pip install n3rv                          # from PyPI
pip install git+https://github.com/juanmanueldaza/n3rv.git  # from source (latest)
cd your-project
n3rv init

Or install and run in one shot:

pip install git+https://github.com/juanmanueldaza/n3rv.git && n3rv init

n3rv init provisions your workspace with:

📂 Project root
├── 📄 AGENTS.md              # Coding standards with LCL-injected project context
├── 📄 opencode.json          # opencode config: MCP servers, agents, instructions
├── 📄 CONTRIBUTING.md
├── 📄 SECURITY.md
├── 📂 .opencode/
│   ├── 📂 skills/            # 14 skills (code, testing, commits, SDD phases, etc.)
│   ├── 📂 agents/            # 10 sub-agents (SDD phases + git-ops + github-ops)
│   ├── 📂 commands/          # 4 slash commands (sdd-new, judgment-day, review, handoff)
│   ├── 📂 plugins/           # lifecycle & shell-env plugins
│   └── 📂 scripts/           # MCP wrapper scripts
├── 📂 .n3rv/
│   ├── 📄 a2a-config.yaml    # Agent-to-Agent hub configuration
│   ├── 📄 skill-registry.md  # Auto-generated skill index
│   ├── 📂 memory/            # ChromaDB + SQLite (MAGI storage)
│   └── 📂 systemd/           # Background service unit
└── 📂 .githooks/
    └── 📄 pre-push            # Git pre-push hook

🛠️ Usage

n3rv init [--stack python|node|go|generic] [--force]
n3rv update [--dry-run] [--force-commands]
n3rv hub start                          # foreground A2A hub (development)
n3rv daemon install|start|stop|status|enable|logs   # background service
n3rv memory list|search|prune|stats     # MAGI memory operations

MCP Servers (auto-configured in opencode.json)

Server Purpose
n3rv-memory ChromaDB + SQLite dual-store memory
n3rv-hub A2A task delegation (JSON-RPC 2.0)
github GitHub API via MCP
context7 Contextual search across codebase
sequential-thinking Chain-of-thought reasoning

🧠 Memory: The MAGI

Dual-store persistent memory:

  • ChromaDB — Vector embeddings for semantic long-term recall
  • SQLite — Relations between memories (judgments, revisions, verdicts)

Memory types: architecture, bugfix, config, decision, discovery, learning, pattern, context, summary, note.

Scopes: project (shared), session (current), personal (agent-specific).


📋 SDD Workflow

8-phase Spec-Driven Development pipeline, started via /sdd-new <change>:

explore → propose → spec → design → tasks → apply → verify → archive

Each phase is a dedicated skill + sub-agent. Phases write to persistent memory with topic_key: sdd-<change_id>-<phase>.


🗺️ Project Status

N3RV is currently under active development, built in public. We are testing restraint stability and optimizing context-delivery pipelines.

Install or update:

pip install --force-reinstall n3rv      # latest from PyPI
# or from source:
pip install --force-reinstall git+https://github.com/juanmanueldaza/n3rv.git

📄 License

Distributed under the GNU General Public License v2.0 (GPL-2.0). N3RV is copyleft software — keeping the armor open ensures the angels stay contained.


God's in his heaven. All's right with the world.

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