agentic-ecos
Provides tools for ecosystem branch creation, syncing with upstream, and merging changes, ensuring traceable and version-controlled management of the ecosystem and its knowledge.
Facilitates private fork management, pull request workflows, and configuration of GitHub secrets, enabling secure collaboration and integration with GitHub-hosted repositories.
Includes GitHub Actions workflows for automated ecosystem snapshots, weekly summaries, pre-dev verification, knowledge review, and task automation, with optional LLM-powered synthesis and graceful degradation.
Generates Obsidian vaults as part of project initialization and provides tools like vault_query_graph to query the vault's knowledge graph for context-aware interactions.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agentic-ecosInitialize agentic infrastructure for my project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
agentic-ecos
Control plane for traceable agentic infrastructure. agentic-ecos is an MCP
server that bootstraps, manages, and operates multi-agent coordination across
your entire digital ecosystem — not just one project.
It generates the full agentic stack in any project (locks, tasks with kanban, inter-agent communication, session audit, access control, protocol documents, and an Obsidian vault). It maintains a canonical registry of every project in your ecosystem and their agentic health. It encodes 15 battle-tested coordination patterns that agents query to avoid rediscovering the same solutions. And it handles the complete task lifecycle — create, claim, work, complete — with git-based traceability that records who did what and when.
All of this works local-first: agents coordinate via git push rejection, no central server required. GitHub Actions and LLM-synthesized automation are available as an optional layer on top.
Python 3.10+ · git · 37 MCP tools · 85 tests · MIT
Compatible with any MCP client: OpenCode, Claude Code, Cursor, and others
LLM-agnostic automation: DeepSeek, GPT, Claude, Ollama — opt-in
Vault autodocumental abrible en Obsidian (
docs/)
# Fork con nombre propio (universal: funciona para dueño y terceros)
gh repo fork deibanez/agentic-ecos --clone --fork-name agentic-ecos-priv
gh repo edit --visibility private # settings → danger zone → change visibility
cd agentic-ecos-priv && uv add --dev mcp && uv pip install --editable .
agentic-ecos connect --agent auto # sin --target: usa workspace_root de agentic.toml o CWDWhy
You get | Instead of | So you can |
Multi-agent coordination via git | Central servers, lock services | Any agent, any machine, no extra infra |
Task lifecycle with T-ID traceability | Ad-hoc bash + manual git | Know who did what and when |
15 battle-tested agentic patterns | Rediscovering coordination every project | Reuse proven logic |
Automated project bootstrapping | Manual setup of locks/tasks/comms | 42 files generated in seconds |
LLM-agnostic automation (opt-in) | Vendor lock-in | Choose your provider freely |
Related MCP server: orchestrator-mcp
Requirements
Requisito | Mínimo | Nota |
Python | 3.10+ | Compatible con 3.11, 3.12 |
git | Cualquiera reciente | Coordinación agéntica (git push rejection) |
gh CLI | 2.0+ |
|
Instalador |
|
|
Cliente MCP | Cualquiera | OpenCode, Claude Code, Cursor, etc. — agnóstico |
LLM (opcional) | Ninguno | Solo para automatización con síntesis de IA ( |
Instalación de herramientas base (una vez por máquina):
# git (Linux: apt/snap · macOS: brew)
sudo apt install git # o: brew install git
# gh CLI (GitHub CLI)
sudo apt install gh # o: brew install gh
gh auth login # autenticarse (usar HTTPS o SSH)
# uv (gestor de paquetes Python)
pip install uv # o: curl -LsSf https://astral.sh/uv/install.sh | shQuickstart
Setup único — fork privado + instalación
El fork privado cubre ambos casos de uso: las tools del Modo 1 (simple)
funcionan igual en un fork, y habilita el Modo 2 (ecosistema) cuando lo
necesites. Solo main y dev del upstream son públicos — tu ecosistema vive
en el fork privado (trazabilidad completa con git log).
# 0. Fork privado + upstream (una vez) — universal, funciona para dueño y terceros
gh repo fork deibanez/agentic-ecos --clone --fork-name agentic-ecos-priv
gh repo edit --visibility private
cd agentic-ecos-priv
git remote add upstream https://github.com/deibanez/agentic-ecos.git
# 1. Dependencias + CLI (una vez)
uv add --dev mcp
uv pip install --editable .
# 2. Branch de ecosistema (una vez) — trazable, registra en AGENT_SESSION_LOG
agentic-ecos ecosystem branch-create mi-eco --base main
# base=main (estable, recomendado) | base=dev (bleeding edge)
# 3. Plano de control (una vez por ecosistema)
agentic-ecos ecosystem init --name mi-ecosistema --workspace ~/repos
# --workspace = dónde viven tus proyectos (ajustá a tu ruta)
# 4. Conectar el MCP a tu agente (una vez por workspace)
agentic-ecos connect --agent auto
# Sin --target: usa el workspace_root definido por ecosystem_init (paso 3),
# así que escribe opencode.jsonc en la raíz de tu workspace, no en el repo.
# Solo usa --target explícito si querés escribir en otro directorio.
# 5. Verificar
agentic-ecos protocolsUso inmediato (Modo 1 — sin registro de proyectos)
Las tools MCP funcionan inmediatamente tras conectar el server:
# Desde tu agente (con el MCP conectado):
# init_project("mi-proyecto", preset="monorepo", target_path=".../docs")
# list_patterns() → los 15 patrones agénticos
# validate_structure("...") → verifica cobertura agéntica
# protocol_template("agent_protocol") → plantilla de protocoloHow tasks work
Tasks are local-first: they run in your agent session using git for coordination. No central server, no CI/CD required.
flowchart LR
add[ecosystem_task_add] --> backlog[(backlog)]
backlog --> claim[ecosystem_task_claim]
claim --> doing[(doing)]
doing --> done[ecosystem_task_done]
done --> log[(AGENT_SESSION_LOG.md)]Race-free claiming: claim does git commit + git push. If two agents
claim the same task, the second push is rejected — the agent picks another.
Every action is traced with a T-ID.
agentic-ecos ecosystem add-task "Fix staging deploy" --priority high --type ci-cd
agentic-ecos ecosystem task-status --filter unclaimed
agentic-ecos ecosystem claim E1 --agent opencode-nesto
# ... work: changes → verify → commit [agent:: opencode-nesto] ...
agentic-ecos ecosystem done E1 --agent opencode-nestoGitHub Actions is optional: task-automation.yml automates the same cycle
for docs/ops tasks. Not needed for daily agent work — see
CONTRIBUTING.md §9.
Key design
Feature | What it does |
Auto-context on connect | The agent receives instructions in the MCP handshake — no need to memorize the 37 tools. |
Live context in every response | Every MCP tool response carries |
Local-first task lifecycle | Add/claim/done with race-free git push rejection. Every action traced with a T-ID |
4-tier knowledge | Patterns grow: personal → ecosystem → community → built-in |
LLM-agnostic | DeepSeek, GPT, Claude, Ollama — any provider. Works without LLM too (graceful degradation) |
Multi-agent MCP | OpenCode, Claude Code, Cursor — one command: |
Core tools
Category | Tools |
Projects |
|
Ecosystem |
|
Tasks |
|
Knowledge |
|
Git Ops |
|
Full reference: ARCHITECTURE.md §7 documents all 37 tools.
Knowledge lifecycle
flowchart TB
D[discover] --> T3[(data/ tier 3)]
T3 --> V{validated<br/>2+ projects?}
V -->|no| T3
V -->|yes| T25[(workspace/ tier 2.5)]
T25 --> S{shared with<br/>community?}
S -->|no| T25
S -->|yes| T2[(knowledge/ tier 2)]
T2 --> M{mature<br/>enough?}
M -->|no| T2
M -->|yes| T1[(patterns.py tier 1)]Tier | Location | Git | Cycle |
3 · Personal |
| ✓ committed (private fork) |
|
2.5 · Ecosystem |
| ✓ (tu branch) |
|
2 · Community |
| ✓ committed |
|
1 · Built-in |
| ✓ committed | Move to code → everyone |
Solo el runtime data (data/ecosystem-snapshots/, data/state.json) queda
gitignored — no es conocimiento y genera conflictos de merge.
LLM Automation (opt-in)
Set these secrets to unlock AI-synthesized weekly summaries, task proposals, PR reviews and automated task loops:
Secret | Required | Description |
| ✓ | API key del provider |
| ⏸️ | Default |
| ⏸️ | Solo para providers custom |
Degradación elegante: sin LLM_API_KEY, los workflows commitean los datos
crudos sin síntesis. El sistema nunca falla por LLM no configurado.
See CONTRIBUTING.md §9 for the full CI/CD setup.
CLI reference
# Projects
agentic-ecos init mi-proyecto --preset monorepo --repos api,frontend
agentic-ecos validate ./ruta/al/vault
# Ecosystem
agentic-ecos ecosystem init --name eco --workspace ~/repos
agentic-ecos ecosystem status
agentic-ecos ecosystem add otro-svc --type frontend
# Tasks (local-first)
agentic-ecos ecosystem add-task "Migrar satet" --priority high --type iac
agentic-ecos ecosystem claim E1 --agent opencode-alpha
agentic-ecos ecosystem done E1 --agent opencode-alpha
agentic-ecos ecosystem task-status --filter unclaimed
# Git ops (traceable)
agentic-ecos ecosystem branch-create mi-eco --base main
agentic-ecos ecosystem sync --branch main
agentic-ecos ecosystem merge-main --target ecosystem/mi-eco
# Knowledge
agentic-ecos promote mi-pattern --to workspace
agentic-ecos promote mi-pattern --to knowledge --source workspace
agentic-ecos knowledge status
# Automation (JSON output for CI)
agentic-ecos ecosystem status --json
agentic-ecos llm-test --prompt "Hola"Presets
monorepo— múltiples servicios con CI/CD compartido e IaC centralizadasingle_service— un servicio con componentes en subdirectoriosdata_pipeline— lambdas, jobs batch, pipeline de ingesta/procesamiento
Structure
agentic_ecos/
├── server.py # MCP server (37 tools)
├── generator.py # init_project + generate_file + validate + CLI
├── patterns.py # 15 patrones agénticos (tier 1)
├── protocols.py # 5 plantillas de protocolos
├── presets.py # monorepo / single_service / data_pipeline
├── ecosystem.py # plano de control (agentic.toml, connect, tasks)
├── storage.py # data/ + knowledge/ + workspace/ carga/guardado
├── knowledge.py # promoción entre tiers
├── llm.py # motor de síntesis LLM agnóstico
├── task_loop.py # desarrollo continuo (detect→claim→plan→execute→verify)
├── knowledge/ # tier 2 · comunidad
├── data/ # tier 3 · personal (snapshots/state gitignored)
├── static/ # scripts copiados tal cual a cada proyecto
└── templates/ # plantillas markdown generables
.github/workflows/ # 5 workflows de automatización
workspace/ # tier 2.5 · solo en branches de ecosistema
docs/00_Global/ # vault autodocumental (Obsidian)Docs
ARCHITECTURE.md — capas, patrones, plano de control, pipeline de generación
CONTRIBUTING.md — uso, forking, ciclo del conocimiento, privacidad, CI/CD
instructions.md — prompt del agente
LICENSE — MIT License
Roadmap
Task loop scheduling (actualmente solo
workflow_dispatch)RAG opt-in para vaults grandes
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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