Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Local memory for Claude Code: 13 MCP tools for semantic recall, file replay, and git history.
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.
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": {
"longhand": {
"command": "uvx",
"args": [
"longhand",
"mcp-server"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add longhand -- uvx longhand mcp-serverIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"longhand": {
"command": "uvx",
"args": [
"longhand",
"mcp-server"
]
}
}
}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": {
"longhand": {
"type": "stdio",
"command": "uvx",
"args": [
"longhand",
"mcp-server"
]
}
}
}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.
Diese 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 Wynelson94 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 (1.3.1) kam vorgestern 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.
Using Codex too? Share one memory archive between Claude Code and Codex.
Persistent local memory for Claude Code. Every tool call, every file edit, every thinking block from every Claude Code session — stored verbatim on your machine. Searchable, replayable, and recallable by fuzzy natural-language questions. Zero API calls. Zero summaries. Zero decisions made by an AI about what's worth remembering.
Claude Code quietly rotates your session files after a few weeks. Longhand captures them into SQLite before they're gone. Once ingested, your history stays forever — even after the source JSONL files are deleted. Install early; the past you don't capture is unrecoverable.
If you have 20+ Claude Code sessions in `~/.claude/projects/`, Longhand can search across every fix, decision, and conversation you've had in ~29ms — without a single API call.
Does it use a lot of tokens? No — the tools you'll use most are capped by design. A full
recallacross 100+ sessions returns ~4K tokens. Reading one raw session JSONL costs 10–50× more. See Token budget for which tools cap output and which don't.
pip install longhand
longhand setup # ingest history + install hooks + configure MCP longhand recall "that stripe webhook bug from last week"
Want to kick the tires first? Run longhand demo for a 60-second walkthrough on a fake 3-session sample corpus — your real ~/.claude and ~/.longhand are not touched. The demo seeds a sandboxed store with a Stripe-webhook bug + Supabase auth migration + downstream 401 fix, then runs cross-session recall and project-status so you can see what the output looks like before committing.
pip install longhand
longhand demo # sandboxed; cleans up afterwards (pass --keep to explore)
Upgrading to 1.0.0? This is the release that closes the deprecation window 0.13 opened. Everything removed here has been warning since 0.13.0:
patterns → recall " ", recap → status --days N, continue → status --session , reanalyze → analyze --all.fix=true explicitly. Dry runs tell you so in the payload.CLAUDE.md files and must never hard-fail.Your database needs nothing. Migrations are automatic and a 0.11+ store opens on any later 1.x — that's Promise 2, and there's a real 0.11-schema fixture in the test suite proving it.
Upgrading to 1.3.0? Nothing removed, and nothing changes until you ask for it. One new, opt-in capability: longhand backup writes every session's verbatim transcript to a private git repository you own (secret-shaped strings masked in the copy only), and longhand restore rebuilds the archive on a new machine from it. It stays off until backup init has shown you exactly what would be uploaded and you have typed yes. See Backup below and docs/backup.md.
Upgrading to 1.2.x? No removals, just fixes worth knowing about:
get_session_timeline's tail now returns the true last N events on sessions over 5,000 events — it used to return the middle. setup's closing hint stopped suggesting recap (removed at 1.0) and now suggests status --days 7. Recall's footers and get_session_timeline's own tool description stopped naming search_in_context (retired from the tool listing at 1.0, though it still answers) and now point at search — the footers spell out the call, search(session_id=…, query=…, context_events=5).recall says so when its top match is much older than the alternatives instead of letting a stale fix read as current (see Recall Example). A Codex context-compaction record (compacted) no longer trips doctor's transcript-format-drift warning.get_session_timeline had a sentinel bug that made every call return exactly one event, ignoring limit/offset, unless tail was passed explicitly — fixed. search's project auto-scoping no longer overrides an explicit session_id.Upgrading to 0.13.0? Nothing breaks — that release opened the v1.0 deprecation window, so every old name kept working while pointing at its replacement:
status is now the single resume command: bare status = recent digest (was recap), status unchanged, status --session = session tail (was continue). The old commands still run and print a pointer; they're removed at v1.0.search_in_context → search + context_events, get_episode → find_episodes + episode_id, etc. — full table in the CHANGELOG). The retired names still answer, prefixed with a migration note.~/.longhand/logs/ and two new doctor rows (Hook errors, Transcript format) keep them visible.LONGHAND_DATA_DIR relocates the store for the CLI, hooks, and MCP server in one move — except longhand config --set, which always writes ~/.longhand/config.json regardless of the relocated store (#96; --edit is currently a no-op, same issue). status --json / doctor --json for scripting.Upgrading to 0.9.0? Live ingestion captures sessions in flight, plan history is preserved as first-class data, and an optional reconciler job keeps the index honest in the background:
longhand ingest-live command runs from Claude Code's Stop hook to tail the active transcript between assistant turns. The in-progress session becomes queryable immediately via list_sessions, get_session_timeline/timeline, get_file_history, and replay_file — it writes events only, no embeddings, so recall and semantic search still need the SessionEnd pass (or a reconcile --fix pass, which re-ingests with analysis) to see it.longhand plans list command and list_plans MCP tool surface every Write/Edit to ~/.claude/plans/*.md across your entire history. Plans are now extracted as their own entity alongside episodes.longhand schedule install-reconciler installs an optional launchd job that runs reconcile --fix periodically — catches anything the live and post-session hooks missed without you ever thinking about it.Upgrading to 0.8.1? Staleness signals now propagate everywhere they belong, and reconcile is an MCP tool — Claude can self-heal the index from inside a session:
search and list_sessions now wrap the response with stale: true + stale_reason when the project they're scoped to has on-disk transcripts not yet ingested. Pre-v0.8.1 these returned clean-looking empty results (same silent-failure shape recall_project_status was built to catch — just one layer up).reconcile MCP tool wraps longhand reconcile --fix. After a staleness banner fires, Claude calls reconcile directly instead of asking the user to run a CLI command.list_sessions default limit raised from 20 to 50 — active days routinely cross 5+ projects across 5+ sessions; the old default truncated reviews silently.Upgrading from 0.7.x or earlier? Cleaner recall narratives, plus a real bug-finding test layer underneath (from 0.8.0):
_compose_fix_summary prepended a literal "Intent:" label to half of all extracted episodes (49% of the reference corpus). The label leaked into every recall narrative for those episodes. Migration v4 strips it from existing rows on first store open — no command needed.fix_summary now truncates at whitespace boundaries with a visible …, instead of landing mid-token (phoneNum', family?:', strin'). Forward-only.tests/fixtures/corpus/) anchors regression tests to real shipped bugs. New recall validator (scripts/recall_diff.py) snapshots and diffs ranking results against your live corpus — catches regressions pytest can't see.pip install --upgrade longhand
longhand recall "..." # migration runs transparently on first open
If you're also coming from 0.5.x, run longhand reconcile --fix once to re-attribute multi-project sessions per the v0.6 inference improvements (cd-into-project sessions now attribute to the project where most work happened, not the first-event cwd). If you're on 0.5.8 or earlier, chain them: longhand reconcile --fix && longhand analyze --all. Both are idempotent.
Large history? (>1 GB of `~/.claude/projects`) Expect the first-time backfill to take 10–30 minutes on an M-class Mac — most of that wall time is the embedding model running on all your cores (which is why you'll see triple-digit CPU%; that's ONNX doing its job, not a hang). --skip-analysis defers the *other* pass — episode/segment extraction and project/session-level vectors — not event embedding, which always runs, so it trims some time but not the dominant cost:
longhand setup --skip-analysis # events stored + embedded; episodes/segments deferred
longhand analyze --all # fill in episodes + segments + project/session vectors whenever, safe to background
search, timelines, file history, and commit lookup all work immediately after --skip-analysis — every event is embedded regardless of this flag. recall's episode/segment narrative and recall_project_status need the analyze --all pass to have data to draw on. Typical throughput on an M-class Mac is ~1–2 sessions/sec for full analysis.
*Status: v1.3.1 — stable, daily-driver tested, security-audited (zero critical findings), on PyPI, available as a Claude Code plugin. Validated against 792 real sessions (786 Claude Code, 6 Codex) across 45 inferred projects (measured 2026-09-27). 834 unit tests passing.*
Full docs: Longhand Wiki — getting started, CLI reference, MCP tools reference, architecture, and troubleshooting.
Everyone is solving AI memory by making the context window bigger. 1M tokens. 2M tokens. Context-infinite. The whole industry is racing in the same direction: make the mod
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