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    Veedubin

    Neuralgentics

    v0.16.5MCP Integrations
    @veedubin/neuralgentics

    Neuralgentics OpenCode plugin — agent personas, skills, routing enforcement, and MCP tools.

    GitHub stars

    0

    Monthly installs

    4,619

    169 in 7 days

    Composite scoreSCORE

    42.5

    Multi-signal model

    Last commit

    2 hours ago

    2026-08-20

    Install and configure

    opencode.json

    Writes to this project's opencode.json — applies to this repository only.

    opencode.json

    {
      "$schema": "https://opencode.ai/config.json",
      "plugin": ["@veedubin/neuralgentics@0.16.5"]
    }

    opencode loads npm dependencies through its embedded runtime on startup and caches them locally — no manual global install needed.

    Agent orchestration for OpenCode — 12 agent personas, 7 skills, 9 MCP servers, one plugin.

    Ecosystem

    Neuralgentics is the orchestration hub for a modular agent ecosystem. The diagram below illustrates how Neuralgentics integrates with its sibling projects to provide a seamless, scalable, and secure agentic workflow:

    flowchart LR
        U[User] -->|prompt| OC[OpenCode TUI]
        OC -->|task| ORCH["Neuralgentics Orchestrator<br/>12 personas + routing matrix"]
        ORCH -->|query / save| MEM[("memini-ai<br/>FIRST-CLASS MCP<br/>registered directly in opencode.json")]
        MEM --> PG[("PostgreSQL + pgvector<br/>trust-weighted memory")]
        ORCH -->|dispatch| AG["Specialist sub-agents<br/>coder · architect · tester · writer"]
        AG -->|"long-tail tool calls"| BRK["Neuralgentics Broker<br/>catalog · access control · audit"]
        BRK --> MCP["Brokered MCP servers<br/>searxng · github · videre · ssh<br/>behind the broker · on demand"]
        AG -->|outbound HTTP| GW["Neuralgentics Gateway<br/>egress policy + audit"]
        GW --> NET["Internet / LLM APIs"]
        MEM --> WEB["Neuralgentics Web<br/>dashboards"]
        GW --> WEB
        BRK --> WEB
    

    memini-ai is a first-class MCP server — registered directly in opencode.json and always loaded. Every other MCP server sits behind the broker: catalog-advertised, access-controlled, and brokered on demand, which keeps long-tail tool schemas out of every prompt.

    Sibling Projects

    Features

    Neuralgentics provides a comprehensive, modular, and secure agent orchestration platform:

    Orchestration

    • 12 specialized agent personas: Orchestrator, architect, coder, explorer, tester, reviewer, linter, git, writer, researcher, release, and agent-builder.
    • Routing matrix: Enforces strict delegation rules to prevent context loss and ensure optimal agent selection.
    • Parallel dispatch: Launches multiple sub-agents simultaneously for independent tasks, reducing latency.

    Memory Integration

    • memini-ai integration: Trust-weighted semantic memory with PostgreSQL + pgvector backend.
    • Trust scoring: Memories are scored based on usage and feedback, ensuring high-trust context is prioritized.
    • Tiered loading: Efficient context management with L0 (~100 tokens), L1 (~2K tokens), and L2 (full context) summaries.
    • Knowledge graph: Tracks entities and relationships for advanced reasoning and inference.

    Skills Brokering

    • Local + external skills: Access to ~400 skills with provenance tracking, LRU caching, and auto-evolution gates.
    • Broker-mediated tool calls: MCP tools are provisioned dynamically with access control and audit logging.
    • Token efficiency: ~95% reduction in token usage by replacing inline ContextPackages with memory IDs.

    Broker

    • Tool audit: Tracks MCP tool usage, access patterns, and anomalies.
    • Access control: Fine-grained permissions for MCP tools and external APIs.
    • Provenance tracking: Ensures all tool calls are traceable and reproducible.

    Gateway

    • Egress policy: Enforces security and compliance for outbound HTTP requests.
    • Audit logging: Tracks all external API calls for security and debugging.

    Web

    • Dashboards: Real-time visualization of memory, broker, and gateway activity.

    Installer

    • Zero-Docker database: Built-in PostgreSQL via pgembed — no Docker required.
    • Flexible initialization: --init-homedir for global config, --init-project for project-specific setup.
    • Team server support: Connect to shared PostgreSQL for collaborative memory.
    • Embedding model selection: CPU, Auto (GPU-aware), or GPU modes for optimal performance.

    Quick Start

    # 1. Install global config (provider, MCP servers, agents, skills)
    npx @veedubin/neuralgentics --init-homedir
    
    # 2. In your project directory, install project config + database
    cd my-project
    npx @veedubin/neuralgentics --init-project
    
    # 3. Launch opencode (the installer offers to do this for you)
    opencode
    

    That's it. The built-in database (pgembed) needs zero Docker — it just works.

    What the installer does

    --init-homedir

    Installs to ~/.config/opencode/ (Linux) or ~/Library/Application Support/opencode/ (Mac):

    • Provider config — Ollama Cloud with 10 models pre-configured
    • 9 MCP server templates — videre-mcp enabled, rest disabled (enable what you need)
    • 12 agent personas — orchestrator, architect, coder, explorer, tester, reviewer, linter, git, writer, researcher, release, agent-builder
    • 7 skills — kanban-board-manager, todo-list-updater, skill-self-audit, orchestrator, handoff, external-skills-fetcher, update-gh-docs
    • 7 slash commands/handoff, /orchestrator, /kanban-board-manager, /skill-self-audit, /todo-list-updater, /update-gh-docs, /external-skills-fetcher
    • AGENTS.md — project instructions and agent protocol
    • Pre-downloads all MCP packages via uvx/npx so first launch is fast

    --init-project

    Installs to ./.opencode/ (or --target <dir>):

    • Plugin registration@veedubin/neuralgentics in the plugin array
    • memini-ai-dev MCP server — enabled with your chosen database backend
    • Same agents, skills, AGENTS.md as homedir (or project-specific overrides)
    • Database setup:
      • Built-in (pgembed): Zero Docker. Uses a local Unix socket — no username or password needed. Data stored in ~/.local/share/memini-ai/pgembed/data.
      • Team server: Connects to a shared PostgreSQL. Asks for host, port, database name, username, and password. Saves credentials to .env. The installer does NOT probe or migrate the team database — it just writes the config. memini-ai auto-creates its tables on first launch. Make sure PostgreSQL is running before launching opencode (run npx @veedubin/neuralgentics --db-start if you need a local server).
    • Offers to launch opencode when done

    Interactive Prompts

    Running npx @veedubin/neuralgentics --init-homedir without skip flags walks you through:

    1. How should memini-ai store memories?
      • 1. Built-in database (recommended) — No setup needed, everything runs locally.
      • 2. Team server — Connect to a shared PostgreSQL database for team memory.

    Team Server, RBAC, SSL, and Containers

    memini-ai-dev supports team server mode with per-project PostgreSQL users, SSL/TLS, and container runtime detection.

    Default behavior: All users have read/write/edit access to all memories (open by default). Per-project isolation is opt-in via MEMINI_PEER_ENFORCEMENT=true.

    For full documentation on RBAC user management, SSL configuration, and container runtime setup, see the memini-ai-dev README.

    Neuralgentics inherits all of memini-ai-dev's team server capabilities. The --team flag during neuralgentics --init-homedir or --init-project passes through to memini-ai-dev's installer.

    1. Team server setup (only if you chose team server) — connect-to-existing only:

      • Server IP/hostname (default: localhost)
      • Port (default: 6200, matching the shipped docker-compose.yml)
      • Database name (default: neuralgentics)
      • Username (default: neuralgentics)
      • Password (you enter)
      • Save credentials to .env? (default: yes)
      • Don't have a PostgreSQL server yet? Run npx @veedubin/neuralgentics --db-start first — it ships a compose file + example env, brings the stack up, and offers to create your first database user. See the overlay README's "Team server mode (connect-to-existing)" section.
    2. What embedding model should memini-ai use?

      • 1. CPU — Fast and lightweight, runs on any machine.
      • 2. Auto (recommended) — Same as CPU by default, can upgrade to higher quality if you add a GPU later.
      • 3. GPU — Highest quality, but requires a dedicated GPU (NVIDIA CUDA or Apple Silicon MPS).
    3. Want to add your Ollama Cloud API key now?

      • Get one at https://ollama.com (free tier available).
      • You can skip and add it later to ~/.config/opencode/.env.

    System Dependencies

    The installer checks for required tools before writing anything:

    Tool Required for Install
    uv Python MCP servers (memini-ai-dev, videre-mcp, markitdown, duckdb) curl -LsSf https://astral.sh/uv/install.sh | sh (Linux) or brew install uv (Mac)
    node Node MCP servers (ssh-mcp, playwright, github-mcp, searxng, calculator) https://nodejs.org/
    npx Same as above (ships with Node.js) https://nodejs.org/
    libgl1 videre-mcp vision (Linux only) sudo apt-get install -y libgl1 libglib2.0-0
    libglib2.0-0 videre-mcp vision (Linux only) Same as above

    If any required tools are missing, the installer prints the install commands and exits. Nothing gets written until deps are satisfied. Missing ML libs (for videre-mcp) are non-blocking — everything else works without them.

    Flags

    Flag Purpose
    --init-homedir Install global config
    --init-project Install project config
    --init Alias for --init-project
    --update Update ALL installs (projects + homedir)
    --update-project Update just this project
    --update-homedir Update just the home dir
    --embedded Skip backend prompt, use built-in database
    --team Skip backend prompt, use team server
    --CPU-Embed Skip embedding prompt, use CPU mode
    --Auto-Embed Skip embedding prompt, use Auto mode
    --GPU-Embed Skip embedding prompt, use GPU mode
    --yes Skip all prompts (use defaults)
    --target <dir> Override install target directory
    --dry-run Print what would happen without writing anything

    MCP Servers

    9 servers are configured. All use uvx (Python) or npx (Node) so you get the latest version on each launch. Packages are pre-downloaded during install so first launch is fast.

    Server Enabled by default What it does
    memini-ai-dev Project only Semantic memory, trust scoring, knowledge graph
    videre-mcp Homedir Vision: OCR, image description (Florence-2 / PaddleOCR)
    ssh-mcp-server No SSH remote command execution
    markitdown No File conversion: PDF/DOCX/HTML to Markdown
    playwright No Browser automation
    github-mcp No GitHub repos, issues, PRs (needs GITHUB_PERSONAL_ACCESS_TOKEN)
    duckdb No In-memory SQL via DuckDB
    searxng No Web search (needs local SearXNG at http://localhost:8080 — see install docs)
    calculator No Math evaluation

    Enable a server by editing your opencode.json and setting enabled: true.

    Agents

    Agent Model Role
    orchestrator kimi-k2.6 Main coordinator, delegates to sub-agents
    architect deepseek-v4-pro System design, trade-off analysis, research
    coder glm-5.2 Fast code generation, bug fixes
    explorer devstral-2:123b Codebase exploration, file finding
    tester deepseek-v4-flash Test writing, test execution
    reviewer deepseek-v4-pro Code review: logic, security, consistency
    linter qwen3-coder-next Mechanical linting: ESLint, Ruff, mypy, tsc
    git minimax-m3 Version control: commits, branches, tags
    writer mistral-large-3:675b Documentation, markdown
    researcher qwen3.5 Web research, data gathering, scraping
    release devstral-small-2:24b Version bumps, changelogs, tagging
    agent-builder glm-5.2 Pattern detection, skill/agent creation

    Model names in agent files use ollama/<model> format. To use a different provider, see the provider switching guide.

    Cross-Platform

    • Linux: ~/.config/opencode/ for global config
    • Mac: ~/Library/Application Support/opencode/ for global config
    • Windows: Use WSL (treated as Linux)

    Update

    # Update everything (global + all projects)
    neuralgentics --update
    
    # Update just this project
    neuralgentics --update-project
    
    # Update just the home dir
    neuralgentics --update-homedir
    

    The update flow:

    1. Updates config files — opencode.json, agent personas, skills, AGENTS.md from the latest release. Old files backed up to opencode-bak/ before overwrite.
    2. Checks system dependencies — offers to install missing system packages (same as init).
    3. Offers to refresh MCP packages — re-downloads all MCP servers via uvx/npx so they're at the latest version.

    Since we're not deleting (just moving to opencode-bak/), running from the wrong directory is safe.

    Manual install (alternative)

    Add @veedubin/neuralgentics to your .opencode/opencode.json plugin array:

    {
      "plugin": ["@veedubin/neuralgentics"]
    }
    

    Then run opencode to load the plugin.

    Documentation

    For full documentation, visit the Neuralgentics Documentation Site.

    Links

    Resource Link
    Source github.com/Veedubin/neuralgentics
    npm @veedubin/neuralgentics
    License MIT
    Documentation veedubin.github.io/neuralgentics

    License

    MIT licensed. See LICENSE.