Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Git-native, review-gated knowledge base for LLM agents. Cited retrieval, audited writes.
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.
VOUCH_KB_PATHDu 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": {
"vouch": {
"command": "uvx",
"args": [
"vouch-kb",
"serve"
],
"env": {
"VOUCH_KB_PATH": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add vouch --env VOUCH_KB_PATH=your-value -- uvx vouch-kb serveTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"vouch": {
"command": "uvx",
"args": [
"vouch-kb",
"serve"
],
"env": {
"VOUCH_KB_PATH": "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": {
"vouch": {
"type": "stdio",
"command": "uvx",
"args": [
"vouch-kb",
"serve"
],
"env": {
"VOUCH_KB_PATH": "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.
VOUCH_KB_PATH 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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto vouchdev 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.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
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 (1.2.2) kam vor 4 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) 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
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Git-native, review-gated knowledge base for LLM agents. MCP server + JSONL tool server + CLI.
Agents should not start every session with amnesia — but they shouldn't get to write whatever they want either.
vouch gives LLM agents durable memory with an explicit review gate: sessions capture themselves, agents *propose* writes, and nothing becomes durable knowledge until you approve it. Approved artifacts are plain files under .vouch/ — YAML claims, markdown pages — so the KB lives in your repo, is reviewed like code, diffs cleanly, and travels with git clone.
The destination is the one Andrej Karpathy's llm-wiki idea file sketches: stop using LLMs as search engines that rediscover your documents on every question — use them as tireless knowledge engineers that compile, cross-reference, and maintain a living wiki, while humans curate and think. vouch is that idea with the write path made trustworthy. vouch compile has an LLM draft the topic pages, but every page cites approved claims, every [claim: …] citation is machine-verified before the draft is filed, and the drafts pass through the same review gate as every other write. The LLM compiles; the human approves; the wiki compounds.
Often true — and worth being honest about. If you want your agent to remember things, a paragraph in CLAUDE.md, a memory file, or your host's built-in auto-memory gets you most of the way, costs nothing, and needs no install. Reach for that first. Recall is not a hard problem.
What is hard is *trust in the write path*, and that's a different problem than memory. Single-writer memory needs no trust model: you're the only author, and a bad line costs you a shrug. The moment writes come from more than one author — several agents, a teammate, a future you who forgot the context — the question stops being "what did we say?" and becomes "who decided this was true, on what evidence, and can I audit it later?" A prompt cannot answer that, no matter how good the prompt is.
That's the whole of vouch:
| one prompt / memory file | vouch | |
|---|---|---|
| Who can write | whatever the agent decides to save | agents *propose*; a human approves — nothing else lands |
| Why believe a line | vibes | every claim cites a content-hashed source; uncited is a validation error |
| When it's wrong | edit and hope | supersede / contradict / archive, with the old version still in history |
| Who changed it | file mtime | append-only audit log: who proposed, who approved, citing what, when |
| At n ≥ 2 writers | last write wins, silently | one gate, one reviewed history, shared by git clone |
| What you read | a growing pile of notes | compiled topic pages with verified citations — a wiki, not a log |
The same argument as a picture — at one writer the two are the same thing; the gap opens at the second writer and only widens:
So the honest pitch: vouch is not a better place to put memory — it's a review gate in front of one, and a wiki on the other side of it. If you're solo and happy, one prompt is genuinely fine; vouch's session capture runs passively alongside whatever your host already remembers, rather than replacing it. But once a fleet of agents writes to shared knowledge — or a team does — that pile of notes needs an editor, and an editor is not something you can prompt your way to. The case in full: docs/review-gate.md.
For the full UI experience (recommended first time):
docker run --rm -p 127.0.0.1:5173:5173 -v vouch-demo-data:/data ghcr.io/plind-junior/vouch-demo
Pre-seeded KB + full webapp console, zero setup. Pass -e ANTHROPIC_API_KEY=sk-ant-... to enable LLM features.
For the full UI without Docker — Python only, no clone, no node:
pipx install 'vouch-kb[web]' # the browser console ships inside the wheel
vouch serve --transport http --port 8731 & # a backend for the current .vouch/ vouch console # console at http://localhost:5173 — connect it to :8731
vouch console serves the same React console as the Docker demo, straight from the installed package.
For CLI + Claude Code integration (most common ongoing workflow):
# one-liner (Linux + macOS) — picks a Python, ensures pipx, installs vouch-kb
curl -fsSL https://raw.githubusercontent.com/vouchdev/vouch/main/install.sh | sh
vouch)pipx install vouch-kb
The one-liner is POSIX sh and never needs sudo — inspect install.sh first if you'd like.
For MCP server or CLI-only use:
docker run -i --rm -v "$PWD:/data" ghcr.io/vouchdev/vouch:latest # stdio MCP server
docker run --rm -v "$PWD:/data" ghcr.io/vouchdev/vouch:latest status # any CLI command
For local development — CLI and webapp, both running from source:
git clone https://github.com/vouchdev/vouch
cd vouch python3 -m venv .venv && source .venv/bin/activate pip install -e '.[dev,web]' # dev,web is what CI installs — make check needs both vouch --version # the CLI now runs straight from src/ — edits apply without reinstalling
make console # webapp in dev mode: vouch backend on :8731 + live-reload
make check # the CI gate: lint + type + test
make console needs node — it starts vouch serve --transport http and the Vite dev server as a pair, installing the console's node deps automatically on first run. To instead serve the console the way a release wheel does (no dev server), run make webapp-build once, then vouch console. See CONTRIBUTING.md for the full dev workflow.
After exploring the demo above, set up vouch in your own project:
1. Set up the KB and wire Claude Code (one command, one-time, per repo):
cd /path/to/your/project
vouch install-mcp claude-code # creates .vouch/ (if missing) + wires Claude Code
install-mcp initialises the KB when no .vouch/ is discoverable (pass --no-init to skip; vouch init still exists for KB-only setup), then writes .mcp.json (the kb.* MCP tools), the /vouch-* slash commands, and the weight-bearing hooks — SessionStart recall, UserPromptSubmit per-prompt recall, SessionEnd rollup. Per-tool PostToolUse observe / Stop answer are opt-in (capture.realtime; default off). It also registers vouch as a local-scope MCP server in ~/.claude.json (the ⚑ line in the output). Reload your editor window (VS Code: *Developer: Reload Window*) so it loads.
Why the extra registration? A committed
.mcp.jsonis a *project*-scope server, and Claude Code only loads one after a per-user approval — which the VS Code extension never prompts for, so.mcp.jsonalone leaves thekb_*tools invisible in the extension (they sit at "pending approval", while the hooks quietly work — easy to misread as "connected"). The local-scope entryinstall-mcpwrites is trusted on sight, so a fresh install just connects. Verify withclaude mcp list(vouch … ✔ Connected). Pass--no-approveto skip it and approve.mcp.jsonyourself.
What you'll see. Every prompt is checked against the KB first. When vouch knows something relevant, the answer opens with "From vouch memory:", grounded in the cited items; when it doesn't, it opens with *"Nothing in vouch on this."* — recall is visible on every turn, never silent. (A fresh KB knows almost nothing yet: work a session or two so capture fills it, then ask about the project again.)
Prefer one install for every project?
vouch install-mcp claude-code --globalwires vouch once, machine-wide: user-level hooks and commands in~/.claude/plus a user-scope MCP server in~/.claude.json. Every Claude session in every folder then captures + recalls into *that folder's own*.vouch/— data stays per project. Runvouch initonce in each project you want vouch in; by default a folder without a KB never captures anywhere — its session opens with a one-line "runvouch initto enable durable memory here" note and thekb_*tools say the same. Safe next to existing per-project installs: duplicate hooks collapse and capture dedups by event id.
Optionally, a personal catch-all KB. The global install asks one question (or pass
--personal-fallback; later:vouch hub init-personal --fallback): opt in, and folders *without* a project KB capture into a personal KB at~/.local/share/vouch/personalinstead of nowhere — each captured source stamped with the folder it came from, and the session banner saying exactly where the knowledge is going. It is one store shared by every KB-less folder: recall in any of them reads the whole personal KB, so knowledge captured while working in one such folder can surface in another (the injected block says so). Projects with their own.vouch/are never affected. When such a folder later becomes a real project,vouch init+ `vouch adopt` moves its captures into the new project KB *through that KB's own review gate*: sources copy byte-identically, every claim is re-proposed and its byte-offset receipt re-verified, and the project's review config decides durability — adoption never bypasses review. Strictly opt-in; without it, nothing changes.
2. Point `compile` at an LLM — the only step that needs a model. In .vouch/config.yaml:
compile:
llm_cmd: "claude -p --model sonnet"
3. Work a session — it captures itself. Use Claude Code normally. Each tool call is harvested into a gitignored scratch buffer, and at session end the buffer rolls up — mechanically, no LLM — into one pending session-summary page. Never auto-approved: the next session greets yo
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