Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Shared memory, work claims and handoffs so parallel AI coding sessions stop colliding.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
COMMONS_AGENT, COMMONS_TOOLSNecesitas
¿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": {
"commons-memory": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"COMMONS_AGENT",
"-e",
"COMMONS_TOOLS",
"ghcr.io/neoo-blue/commons-memory:0.36.1",
"serve",
"--transport",
"stdio"
],
"env": {
"COMMONS_AGENT": "your-value",
"COMMONS_TOOLS": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add commons-memory --env COMMONS_AGENT=your-value --env COMMONS_TOOLS=your-value -- docker run -i --rm -e COMMONS_AGENT -e COMMONS_TOOLS ghcr.io/neoo-blue/commons-memory:0.36.1 serve --transport stdioCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"commons-memory": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"COMMONS_AGENT",
"-e",
"COMMONS_TOOLS",
"ghcr.io/neoo-blue/commons-memory:0.36.1",
"serve",
"--transport",
"stdio"
],
"env": {
"COMMONS_AGENT": "your-value",
"COMMONS_TOOLS": "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.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"commons-memory": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"COMMONS_AGENT",
"-e",
"COMMONS_TOOLS",
"ghcr.io/neoo-blue/commons-memory:0.36.1",
"serve",
"--transport",
"stdio"
],
"env": {
"COMMONS_AGENT": "your-value",
"COMMONS_TOOLS": "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.
COMMONS_AGENT envCOMMONS_TOOLS envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub Neoo-Blue, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
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.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
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).
El repo de GitHub cambió por última vez –, y la última versión (0.36.1) llegó al registro hace 19 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Docker en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
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
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
Run several Claude Code sessions at once without them redoing or overwriting each other's work.
Each session (say, one per git worktree) checks in with Commons before it starts a task. If another session already has it, it hears so and backs off. Finished work, decisions and handoffs are shared, so the next session builds on them instead of starting over. Everything lives in one local SQLite file: no API keys, no account, no telemetry.
/plugin marketplace add Neoo-Blue/commons-memory
/plugin install commons@commons-memory
Needs uv. Each folder is one agent (claude-code@ ), so run parallel sessions in separate worktrees or checkouts with different folder names.
Two sessions, two worktrees, same task:
claude-code@payments-fix start_work("fix the payments retry", paths=["pay.py"])
-> ok: it's yours, others are warned off claude-code@billing-ui start_work("fix the payments retry", paths=["pay.py"]) -> busy: claude-code@payments-fix has it since 02:33. msg_send them to split it, or wait for their finish_work.
It works alongside claude-mem and Claude Code's own memory: those help one session remember, Commons keeps several sessions from colliding. The plugin lists 19 tools (memory and coordination only). Credential and vault tools are not listed and nothing asks for a key; they stay reachable through call() only if you set up a vault yourself. How it stays safe: docs/threat-model.md.
The same Commons runs as a small self-hosted hub, so sessions on different machines, and other AIs (Codex, Cursor, Gemini CLI, ChatGPT, Grok), share one view of who is doing what.
Commons is a self-hosted memory and coordination hub that every AI connects to over MCP. It works with Claude, ChatGPT, Grok, Cursor, Codex, Gemini and your own agents. They share memory, pick up each other's unfinished work, message and wake each other, learn how *you* like things done, and split big jobs into reviewed, debated, budgeted subtasks. One SQLite file (or Postgres) holds it all. A dashboard shows who is doing what and what it costs.
curl -fsSL https://raw.githubusercontent.com/Neoo-Blue/commons-memory/main/install.sh | sh
irm https://raw.githubusercontent.com/Neoo-Blue/commons-memory/main/install.ps1 | iex # Windows
Docker: see docs/docker.md. Prefer to read it first? curl -fsSLO https://raw.githubusercontent.com/Neoo-Blue/commons-memory/main/install.sh && less install.sh && sh install.sh. No-script alternatives: uvx --from git+https://github.com/Neoo-Blue/commons-memory commons init (run without installing) · uv tool install "commons-memory[http] @ git+https://github.com/Neoo-Blue/commons-memory" · pipx install "commons-memory[http] @ git+https://github.com/Neoo-Blue/commons-memory"
Quickstart · Feature tour · Architecture · Connect any AI · Screenshots · Multi-agent · Security · Networking · Configuration · Troubleshooting · FAQ · Comparison · Roadmap · Changelog
.env.example to .env, create the three secret files it lists (dashboard token, Postgres password, vault key), then docker compose up -d (docker-compose.yml; the comments explain every option).Keys are stored encrypted in the vault and never shown again.
# 1. install (above) — this also runs `commons init` (~/.commons/commons.db)
commons connect claude --platform claude-code # or: cursor | codex | claude-desktop | grok | generic
commons remember "Payments use Stripe webhooks; retries are idempotent" --project shop commons search "how do payments retry"
commons dashboard # http://127.0.0.1:8766
Connect a second AI the same way and it can see the first one's memory immediately. Each client lists only the 32 core tools (6.1k tokens, against 40.4k for all 186); `tools(query)` finds the other 154 and `call(tool, args)` runs them. For other AIs (ChatGPT, Grok, Muse…), paste [the universal prompt](#connect-any-ai).
| Area | What you get | Learn more |
|---|---|---|
| Infrastructure map | One layered map of where everything runs and how it connects: machines, LXCs and VMs, containers, services, URLs and ports, tunnels, storage and bind mounts, repos, systems (e.g. Plex: its parts and the guest each runs on) and the vault credential each uses (name only). Built from a read-only collector (commons infra collect --submit, or commons infra install to run it on a schedule) and from your memories (a small model extracts stated facts, each citing its notes), merged by vmid, IP and URL. Zoomable map, inventory and drawers on the dashboard; agents ask infra("plex") | docs/guide.md |
| Memory & knowledge | Hybrid search (BM25 + local fastembed vectors, entity/time/recency signals, optional rerank) with token budgets · context=N returns the turns around each short hit (a reply needs the turn it answers; a long turn stands alone) and relative dates resolve against each memory's own date ("yesterday (7 May 2023)") · free-text contradiction flags (TypeSafe) · auto-capture hooks for Claude Code/Codex/Gemini/Cursor that keep every message and reply verbatim plus typed observations, and a turn hook for chat apps without hooks (docs/hooks.md) · one graph linking memory, code, sessions, agents · code index (Python, JS/TS, Go, Rust, Java, Ruby, C, C++, C#) plus live definitions, references and types from each language's own server (code_lookup, LSP) · Graphiti adapter (mirror memories into a temporal knowledge graph, bring its facts back) · conflict detection · auto-built, cited knowledge base per project · librarian that tidies and answers find() | docs/tools.md |
| Project board | Every request you make, in your words, with the targets (metric, goal, current), expectations, actions and deliveries under it, layer by layer (project / ui/dashboard). Done needs evidence, dropped needs a reason, and asking twice is counted. It leads every agent's check-in, so nothing you asked for is lost to context compaction or an agent switch. Agents' questions for you wait under "Needs you" and your answer goes straight back to them | docs/tools.md |
| No duplicate work | start_work checks every task against what other agents are doing now and what was finished, so two agents never build the same thing and nobody redoes finished work; hooks run the same check on every message. Each agent gets the Commons routine on its first check-in, so you never have to explain it | PROMPT.md |
| Credential vault | Commons stores your API keys and logins encrypted and makes calls for agents, so no agent ever sees a key, and a key only ever goes to its own service. A decision agent rules on each request: sound reads are allowed, writes need your request behind them, anything destructive or costly comes to you as an approval link the agent hands you: one page showing the exact request, approved with your owner password (agents can't), and approving runs it. Or switch on "approve everything" at your own risk, or always allow one key. It is an order you choose (TypeSafe, any provider you have a key for, a live connected agent on its own subscription, then you), and a phone notification with Yes / No buttons lets you answer anywhere. Agents creating accounts get a generated username and password from the vault · an agent deposits a key the moment it gets one; the base URLs it may go to can follow, and until then it goes nowhere · each key records what it is for, what it can do at the provider, and every place it is installed or used, linked on the infrastructure map, so it can be rotated or narrowed without guessing | CHANGELOG.md |
| Team awareness | A live Team now view (who is working, blocked, done or waiting on you) · a card per agent that the hub writes from what it can check (who issued its key and when, where it runs, how it is woken, its usage headroom, its schedules, the work it finished), kept apart from what the agent claims, with who(name) to read it · agents meet a newcomer at their next check-in instead of a broadcast that would wake and bill every agent, and a newcomer gets the whole team at its first · display names only you set, so grok reads as "Grok bot" while messages still reach it, and no agent can name itself after another · introductions you ask for: one note to each, nobody else woken · every release tells all agents what changed and what to adapt · handoffs carry a commit Commons checks on GitHub · failed CI runs, new issues and new PRs (GitHub watcher or webhook) become jobs for the best live agent | CHANGELOG.md |
| Continuity | Sessions, checkpoints, handoffs that resume in another AI · layered context packs (L0 gist → L3 full) so the next AI doesn't re-pay tokens · decisions with rationale and why() · leftovers and recurring jobs | docs/guide.md |
| Teamwork | Submit a task and it is split for the team: a model plans it (Haiku by default), else a live agent does, else keyword rules, sized to who is live, what each agent is good at and its usage left. Big hand-offs are planned too, and an agent can split a subtask it holds and merge the parts. Six-stage workflow (submit_task(pattern="sdlc") or /sdlc, or one stage with /spec /plan /build /test /review /ship): you approve the spec and confirm the release from the board or your phone, stage leads hand out task cards up to 3 levels deep, each card goes to a cheap, mid or top model and effort by difficulty x criticality (on the agent's own CLI), and the Workflow page shows the stage spine, the agent tree, traceability and tokens saved. Patterns: plan → parallel parts each gated by a review → summary; work → cross-review (author ≠ reviewer); debate → judge; consensus vote. Every job has a shared workspace: each part's result, the code it changed (diff, commit checked on GitHub, also captured by the hooks) and any files, on one timeline with an agent filter. Pin a step to a named agent (retries stay with it), quality gates, budgets, leases with automatic reassignment, an escalation ladder, routing to the right agent + model + effort by strengths, past success, speed, price and usage left, multi-project scheduling, task breakdown view | docs/guide.md, docs/multitasking.md |
| Limits & schedules | Each agent's 5-hour a
Solo se muestra el principio; lee el resto en el repo