Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Self-hosted decision memory for AI coding agents; warns before re-proposing a rejected approach.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
PERCEPTION_API_URL, PERCEPTION_API_KEYAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"robrain": {
"command": "npx",
"args": [
"-y",
"robrain",
"mcp"
],
"env": {
"PERCEPTION_API_URL": "your-value",
"PERCEPTION_API_KEY": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add robrain --env PERCEPTION_API_URL=your-value --env PERCEPTION_API_KEY=your-value -- npx -y robrain mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"robrain": {
"command": "npx",
"args": [
"-y",
"robrain",
"mcp"
],
"env": {
"PERCEPTION_API_URL": "your-value",
"PERCEPTION_API_KEY": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"robrain": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"robrain",
"mcp"
],
"env": {
"PERCEPTION_API_URL": "your-value",
"PERCEPTION_API_KEY": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
PERCEPTION_API_URL envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto adelinamart bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: PERCEPTION_API_KEY
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (2.6.1) kam vor 4 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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Shared memory across your team and your AI agents — with judgment!
RoBrain isn't just another memory layer — it's the brain that helps you and your agents make better decisions and avoid costly mistakes.
Self-hosted on your own Postgres. Passive capture, structured vetoes, corpus-wide contradiction scans — nothing leaves your machine. Works with Claude Code, Cursor, GitHub Copilot (VS Code), Codex CLI, Hermes and more.
Measured: without decision memory, a coding agent re-proposes an approach your team already rejected in up to 9 of 10 tasks. Through RoBrain's full pipeline: 0 of 50, across five archived runs — VetoBench.
RoBrain records what your team and its agents decide — and the alternatives they ruled out — without anyone tagging anything by hand. Sensing captures session turns; Perception extracts each decision into Postgres, where every row can carry a structured rejected[] field.
Most agent-memory tools stop at capture: they store what happened and hope you query it later. RoBrain adds judgment. Batch Synthesis reads the whole corpus to flag contradictions, stance drift, and recurring entities that no single session could see.
The point is the handoff. Someone makes a deliberate call in Cursor on Tuesday — say, keeping Perception on Hono instead of porting to Express. A new teammate opens Claude Code on Wednesday with no memory of it and asks to make exactly that change. RoBrain surfaces the recorded rationale before the agent steers down a path you already rejected — same Postgres store, same vetoes, captured passively.
The cost of forgetting a rejection isn't inefficiency. It's the auth bypass you already patched, the migration you already rolled back, the dependency you already removed for a CVE — re-suggested by an agent with no memory of why you said no.
Coding is the first vertical because the feedback loops are tight — reverts, incidents, and rework make the cost of a forgotten rejection measurable. The same architecture applies wherever agents make decisions that outlast a session.
How it works, the two pillars (capture + judgment), and the full walkthrough: docs/concepts.md.
Two ways to run RoBrain — pick one:
No clone needed — robrain up pulls the published Perception image and generates credentials into ~/.robrain/stack/.env.
Default path uses Anthropic (extraction) + OpenAI (embeddings). Other setups (OpenAI-only, Gemini, other embeddings, fully local) — Concepts — Prefer a different provider setup?.
export ANTHROPIC_API_KEY=... OPENAI_API_KEY=... # or add them to ~/.robrain/stack/.env after the first run
npx robrain@latest up # start Postgres + Perception from ghcr.io npx robrain install --self-hosted # wire Sensing MCP into your editors
From a clone instead (development, or building the image yourself)
First pnpm docker:up auto-creates .env and fills PERCEPTION_API_KEY / POSTGRES_PASSWORD. Perception still needs your LLM + embedding keys before it stays up.
git clone https://github.com/adelinamart/robrain
cd robrain pnpm install && pnpm build pnpm docker:up # first run: creates .env; Perception won't start yet
pnpm docker:up # second run: Perception now boots pnpm robrain install --self-hosted --repo-root "$(pwd)"
pnpm robrain runs the CLI you just built (node packages/cli/bin/robrain.js). Use it instead of npx robrain everywhere in this clone — npx resolves to the published package or a stale global install, not your working tree.
Upgrading a self-hosted install
No-clone stack: re-run npx robrain@latest up (pulls the new Perception image and applies startup DB migrations) then npx robrain@latest install --self-hosted. From a clone: git pull → pnpm install && pnpm build → pnpm docker:up:build → pnpm robrain install --self-hosted --repo-root "$(pwd)" → fully restart editors. Full checklist: CLI reference — Upgrading.
Claude Code users on the self-hosted stack can add hook-based capture and pre-task warnings about previously rejected approaches — no CLAUDE.md protocol needed:
claude plugin marketplace add adelinamart/robrain
claude plugin install robrain@robrain
Details: plugins/claude-code. robrain init-project also recommends the plugin to collaborators via the project's .claude/settings.json, so teammates get an install prompt from Claude Code itself (opt out with --skip-claude-plugin).
On any paid Rory Plans plan, RoBrain runs without hosting anything:
npx robrain install # no flags — cloud mode
Sign in at roryplans.ai, create an API token on your profile page, and paste it when the installer asks. That's the whole setup: no Docker, no database, no LLM or embedding keys — extraction and search run on our side. Your editors (Claude Code, Cursor, Copilot, Codex CLI) are wired automatically, and teammates on your Rory Plans team share the same memory.
Every paid plan qualifies — individual standard or annual, Teams, and enterprise. Solo subscribers get a private memory space; teams share one. Self-hosting stays free and fully supported (see Install above); the comparison table shows what each tier adds.
Cloud also governs memory for production agents: each agent gets its own project (the eve provider registers it on first run), org admins push rules to every production agent or to one kind of agent by tag (npx robrain promote), tags come from the tools an agent uses through an admin-kept mapping (npx robrain tags map), and every governance action is recorded with who did it. The commands are in the CLI reference; self-hosted RoBrain keeps one project by design.
After either install (self-hosted or cloud):
# Wire capture into an application project (run inside the repo)
cd /path/to/your/project npx robrain init-project # writes CLAUDE.md, AGENTS.md, .cursor/rules/robrain.mdc
npx robrain explain path/to/file
npx robrain review
npx robrain synth # drift, contradictions, entity promotion
After init-project, every repo gets CLAUDE.md and AGENTS.md (Codex CLI), and Cursor also gets .cursor/rules/robrain.mdc with alwaysApply: true. If captures don't land, run npx robrain doctor — see Troubleshooting.
By default the classifier stores decisions and the alternatives you rejected, and nothing else. When a project wants more, less, or something different, tell it in plain language. The settings are stored per project on Perception, so every teammate's sessions capture the same way:
npx robrain capture show
npx robrain capture set --instructions "Skip anything about the marketing site. Treat naming conventions as decisions." npx robrain capture set --min-confidence 0.75 # less noise npx robrain capture set --mode broad # every turn reaches the model, not only keyword hits npx robrain capture set --add-kind "run: The outcome of an agent run: what ran, when, and whether it succeeded." npx robrain capture test --file sample-turns.jsonl --compare # dry run before you commit to it
Extra kinds of memory sit beside decisions: each entry names a subject, and a newer entry about the same subject replaces the older one, so a kind can hold changing state (the last run of an agent) as well as rules. Only decisions carry vetoes. Flags and formats: CLI reference.
Every stored decision records who decided it (the git user.email of the session) and when, and the summary and veto warnings say so. Search the memory like a person would, or add a rule without waiting for a session to capture it:
npx robrain search "confirm before sending"
npx robrain rules add "Never auto-send a plan; the customer confirms first." --because "trust" --rejected "auto-send: customers lost drafts"
Hand-written rules are stored like captured ones (same vetoes, summary and review), with confidence 1.0 and approved on insert. A repo gets its own project from init-project; a team that wants one memory across several repos creates a project and pins it in each (npx robrain projects create team-payments, then ROBRAIN_PROJECT_ID=team-payments). The id shapes in use are listed in the naming convention. Upgrades never retire a command or route without a replacement: deprecation policy.
Synthesis runs three passes over the full decisions table — drift (stance moving without an explicit reversal), contradictions (incompatible decisions from different sessions), and entity promotion (recurring tools/patterns condensed into planning_blocks). It writes flags and edges into your DB; it does not capture new decisions — it judges the corpus you already have.
pnpm synthesis:build && pnpm synthesis:run
Review what it finds with npx robrain review. Deep dive (three passes, cron, env vars): Concepts — Synthesis.
One cross-tool setup covers Claude Code, Cursor, GitHub Copilot (VS Code), and Codex CLI against the same Postgres store. The classifier LLM is your choice — Anthropic Haiku or OpenAI. Decisions carry a lifecycle (active / superseded / invalidated) and a graph (conflicts_with / extends / related_to).
Codex CLI / IDE also gets hook-based capture and pre-task veto warnings — the same lifecycle hooks as the Claude Code plugin, wired automatically by robrain install into ~/.codex/config.toml (Codex asks you to trust them on first run). Docs: plugins/codex.
Running Hermes? npx robrain install --hermes drops a standalone memory-provider plugin into ~/.hermes/plugins/ — passive capture and veto-aware recall through the same Perception API. Docs: integrations/hermes.
Decision ledger for git (opt-in):
npx robrain export-memory --ledger
Record the rejection once — RoBrain captures it passively from the session where it happened — and every connected agent gets a veto warning before steering down that path again: the decision, the rejected option, an
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