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Octopus Blackboard

de octorynversión 0.3.1i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.octoryn/octopus-blackboard

Instalar

Resumen

Descripción del creador (original en inglés)

Shared memory & coordination for AI coding agents — a blackboard, not an orchestrator.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Búsqueda y memoria de IA

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "octopus-blackboard": {
      "command": "npx",
      "args": [
        "-y",
        "octopus-blackboard"
      ],
      "env": {
        "OCTOBOARD_AGENT": "your-value",
        "OCTOBOARD_DIR": "your-value"
      }
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add octopus-blackboard --env OCTOBOARD_AGENT=your-value --env OCTOBOARD_DIR=your-value -- npx -y octopus-blackboard

Completa los valores vacíos antes de ejecutarlo.

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "octopus-blackboard": {
      "command": "npx",
      "args": [
        "-y",
        "octopus-blackboard"
      ],
      "env": {
        "OCTOBOARD_AGENT": "your-value",
        "OCTOBOARD_DIR": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "octopus-blackboard": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "octopus-blackboard"
      ],
      "env": {
        "OCTOBOARD_AGENT": "your-value",
        "OCTOBOARD_DIR": "your-value"
      }
    }
  }
}

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Valores que debes completar

  • OCTOBOARD_AGENT env
    Identity the server writes under, e.g. "cursor" or "claude-code". Defaults to "anon".
  • OCTOBOARD_DIR env
    Explicit board directory. Omitted → the server discovers the nearest .octoboard/ by walking up from the working directory.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub octoryn, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Búsqueda y memoria de IAi

  • Más estrellas que el 0% de los otros 7282 servidores de esta categoría
  • Publicado en el registro más recientemente que el 19% de los otros 7282 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 7282 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro Octopus Blackboard?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.3.1) llegó al registro hace 4 meses.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Context7, Codebase Memory, Exa

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

Context7

de upstash

Up-to-date docs for AI agents

Computadora o nube★ 64.224MITActualizado ayer
Instalar

Codebase Memory

de DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Se ejecuta en tu computadora★ 48.148MITActualizado hace 21 días
Instalar

Exa

de exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Se ejecuta en la nube★ 5213MITActualizado el mes pasado
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

Octopus Blackboard

A shared memory and coordination layer for AI coding agents.

Agents do not need another boss. They need a shared blackboard.

简体中文

Part of [Octopus Core](https://github.com/octoryn) — the open infrastructure stack for governed AI. One job per repo, along the agent lifecycle: Scout · Observe · Experience · Blackboard · Workstate · Runtime · Replay — with Inspect governing every stage. The whole stack rides one root primitive — Evidence, the canonical, tamper-evident atom that is the root category everything is built on.

This repo — Blackboard · Coordinate: Shared cognition for coding agents.


Claude Code, Codex, Gemini CLI, Cursor, and your local agents all work on the same repo — but they are blind to each other. One refactors auth while another rewrites the same file. Context is scattered across CLIs. Nobody can replay what happened.

Octopus Blackboard is not an orchestrator. It does not schedule agents, trigger them, or decide anything on their behalf. It is a passive, local-first shared memory that answers six questions:

Who is working on what      →  agents, tasks, claims

What changed → files_changed What was decided → decisions What evidence exists → evidence What risks are open → risks What was left for whom → messages, handoffs

Every agent only needs to be able to read the board, write the board, leave messages, and attach evidence. That's the whole contract.

Why

Enterprises are not primarily afraid that agents aren't smart enough. They are afraid that:

  • Multiple AI tools edit the same code simultaneously
  • Context is scattered across different CLIs
  • There is no shared memory, no audit, no handoff
  • There is no conflict awareness and no way to replay

The blackboard cuts straight through this. Every write appends a tamper-evident, hash-chained entry to an append-only timeline, so the entire history is auditable and replayable — and any after-the-fact edit to an earlier entry breaks verification.

Get Started in 2 Minutes

Blackboard is the easiest way into the Octopus stack — pure coordination memory that works today with just Claude Code and Cursor, no orchestrator required. One command sets everything up:

npx octopus-blackboard quickstart

That single command: creates the local board (.octoboard/) if it isn't there, auto-detects your MCP client (.claude/ → Claude Code, .cursor/ → Cursor, … otherwise a generic snippet), prints the exact paste-ready config for it, and proves the board works with one write + one read.

Then just:

  1. Paste the printed config block into the file it names.
  2. Reload your MCP client (restart it, or reopen the project).
  3. You're done. Ask your agent to call board_status, then board_note "hello" — that's your first board action, on a shared, tamper-evident timeline.

Re-running quickstart is always safe: it never clobbers an existing board or its history. New to the idea of adopting a coordination layer *first*? See Why adopt Blackboard first.

Install

npm install

npm run build # compiles to dist/

Requires Node ≥ 22. The board is a single SQLite file under .octoboard/, discovered by walking up from your working directory (like .git).

See it in action

examples/two-agents.sh plays out the flagship scenario — Claude Code and Codex sharing one board on the same repo: a claim conflict, a live same-file collision, a decision, attribution, a handoff that lands in the other agent's inbox, an AI review, the human-approval CI gate (blocked → passes), the accountability scorecard, blame→narrative, and a verified hash chain with session signatures. Run it in an empty directory:

bash examples/two-agents.sh          # needs `octoboard` on PATH

CLI

octoboard init                                   # create .octoboard/ here

octoboard status # who's on the board, right now

octoboard note "Codex is refactoring auth middleware" octoboard claim trust-layer-policy-schema # claim work; warns on conflict octoboard message claude "Review policy edge cases before merge" octoboard decision "Use hash-chain audit log" --why "tamper-evidence" octoboard risk "Migration may break audit replay" --severity high octoboard file src/auth.ts --change modified --task trust-layer-policy-schema octoboard handoff claude "Tests pass except policy replay" --task trust-layer-policy-schema

octoboard timeline # the full hash-chained history octoboard verify # confirm the chain is intact

Identity is set with --as or the OCTOBOARD_AGENT environment variable. Point at a specific board with --board or OCTOBOARD_DIR.

Conflict awareness

The board never blocks — it *surfaces*. If two agents claim the same key, or touch the same task's files, both writes are recorded and the second agent is warned:

⚠ CONFLICT: "trust-layer-policy-schema" is also held by codex. Both claims recorded.

AI attribution & shared development memory

Git records who *pushed* a commit. It does not record which AI agent produced the code, in which session, on which machine, whether another AI reviewed it, or whether a human approved it. As AI-native development becomes common, accountability must move beyond Git authorship.

The blackboard adds an attribution layer on top of Git — it never rewrites history. Git stays the source of code; the blackboard becomes the source of attribution.

Sessions

A session is one continuous execution of an agent, and the unit attribution hangs off. Starting one makes every subsequent write attribute to it (the active session is remembered across CLI invocations, per agent):

export OCTOBOARD_AGENT=claude OCTOBOARD_PROVIDER=anthropic \

OCTOBOARD_MODEL=claude-opus-4-8 OCTOBOARD_CLI=claude-code

blackboard session start --label "auth work" # captures machine, branch, repo blackboard claim policy-engine blackboard file src/policy.ts --change modified

... make a git commit ...

blackboard link HEAD # attribute the commit's files blackboard session stop

Identity is fully provider-independent — --provider, --model, --cli, or the matching OCTOBOARD_* env vars. Any AI CLI (local or cloud) can register itself with no assumptions about a specific vendor.

Linking commits

blackboard link reads the files a commit touched (via Git) and records one attribution per file for the active session. Optionally it writes an additive git notes entry under refs/notes/blackboard:

blackboard link HEAD --note

blackboard attribute --file src/x.ts --actor human --name Ran # manual

Reviews
blackboard review HEAD --by ai   --name codex --outcome approved --note "tests pass"

blackboard review HEAD --by human --name Ran --outcome approved

Querying the shared memory
blackboard who src/auth.ts             # git authors + AI sessions that touched it

blackboard who src/auth.ts --line 42 # which session introduced this line blackboard explain HEAD # attribution + reviews + related decisions blackboard commits claude-code # which commits came from an AI / CLI blackboard unreviewed # AI commits never reviewed by a human blackboard joint claude codex # files modified by BOTH agents blackboard timeline --session # per-session HH:MM timeline

Example explain:

commit 5fa3095…  Human Dev <a@b.c>  add auth

produced by: ai claude [claude-opus-4-8] — src/auth.ts reviews: human Ran: approved git note: blackboard: produced by claude-code (claude-opus-4-8), session 75b2b7e7…

Every attribution, review, session, and decision is also recorded in the hash-chained timeline, so the full accountability history is tamper-evident and replayable. blackboard and octoboard are the same command.

Governance & accountability chain

The point of attribution is to *enforce* something. The chain from work to a merge gate:

agent work → commit attribution → export/import → CI check → human-review gate
CI gate (check)

Turn queries into an enforceable gate. Read-only — it reports pass/fail and exits non-zero; the CI system decides what to do. The blackboard never blocks.

# In CI, on a PR branch — fail the build if any AI commit isn't human-APPROVED

(a rejected / changes-requested review does not clear the gate):

blackboard check --range origin/main..HEAD --require-human-review echo $? # 0 = pass, 1 = violations

blackboard check --verify-chain --require-attribution --range origin/main..HEAD blackboard check # default gate: verify chain + require human review

Portability (export / import / trailers)

Attribution is local-first; these make it survive git push into a team board or CI:

blackboard export --range origin/main..HEAD --out attribution.json  # on the dev machine

blackboard import attribution.json # on the team board / CI blackboard trailers HEAD # trailer lines for a commit message

import is idempotent (keyed by row id). The bundle carries attributions, reviews, sessions, and related decisions.

Subscribe (watch)

Complete the read/write/subscribe/message contract. Passive: it polls and reports; it never pushes work.

blackboard watch --for claude     # only messages/handoffs/conflicts addressed to me

blackboard watch # the full stream blackboard watch --once # one-shot poll (for scripts)

Signed sessions (sign / verify)

Minimal identity (v0): each session gets an Ed25519 keypair (private key stays local under .octoboard/keys/, gitignored). Signing the timeline head lets verify distinguish trusted state from merely asserted:

blackboard sign        # sign the current head with the active session key

blackboard verify # chain integrity + which sessions have signed, trusted/stale

A session auto-signs its head on session stop. A signature over a head becomes stale the moment any earlier history is altered — so tampering is visible even though the signature itself stays cryptographically valid. This is not yet a full PKI (no key distribution or revocation).

Ingesting CLI transcripts

Populate the board from a CLI's session transcript instead of calling the API by hand — file edits, decisions, and notes flow onto the active sessio

Solo se muestra el principio; lee el resto en el repo

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