Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Beschreibung vom Entwickler (englisches Original)
Long-term memory for Claude: Markdown in a git repo you own. Survives context compaction.
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.
VAULT_DIR, EMBEDDINGSWelche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Die .mcpb-Datei des Entwicklers herunterladen
Der Link führt zur Datei des Entwicklers selbst; wir hosten sie nicht und verpacken sie nicht neu. Öffne die Datei, dann installiert Claude Desktop sie.
Führe das in deinem Terminal aus
Trag die leeren Werte ein, bevor du ihn startest.
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.
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.
VAULT_DIR envEMBEDDINGS 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 AnxovatomicaES 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 (3.9.3) kam vor 19 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du MCPB auf deinem Computer.
In derselben Kategorie: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
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
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
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.
Claude forgets everything when the context compacts. githippo doesn't.
Long-term memory for Claude and any MCP client, stored as plain Markdown in a git repo you own. Hybrid semantic search, a knowledge graph, auto-memory and compaction survival, at about 790 tokens of tool overhead per turn. Every memory is a git commit you can read, diff and revert.
curl -fsSL https://raw.githubusercontent.com/AnxovatomicaES/githippo/main/install.sh | sh
That's the whole install: no account, no token, no questions. It sets up a local memory vault, wires Claude Code (hooks, MCP, status line) and fetches semantic search in the background. Restart Claude Code and just talk; it remembers.
Want it backed up and synced across machines? githippo sync --github creates a private repo with your existing GitHub CLI login and pushes after every change. Just curious? npx -y github:AnxovatomicaES/githippo#v3.9.3 demo shows it working in 30 seconds without installing anything.
one click → use it from claude.ai and your phone
Because each good idea out there lives in a different tool. githippo takes the best of each and fixes the part that hurts:
| Idea | Borrowed from | githippo's twist |
|---|---|---|
| Entities + relations + observations | MCP reference memory server | Entities are Markdown files, relations are [[wikilinks]], and search is semantic, not substring: "the language I prefer" finds "TypeScript" |
| Markdown you can edit, Obsidian graph | Basic Memory | Same human-readable files, but synced through git: every device, full history, zero cloud fees |
Typed relations (works_on [[x]]) | Basic Memory, Dataview | Parsed into a queryable graph; recall follows links one hop automatically |
| Temporal facts ("what was true last quarter?") | Graphiti / Zep | Superseded facts move to a dated History section instead of vanishing, *and* history at= gives exact time travel from git, with no graph DB and no LLM calls |
| Pinned "core memory" blocks | Letta (MemGPT) | Core memory rides inside the MCP server instructions, which live in the system prompt, so it survives compaction in *every* client, including claude.ai |
| Lifecycle hooks around compaction | claude-mem | The PreCompact hook builds the checkpoint deterministically from the transcript (goal, todo state, files changed, where it stopped). No LLM, no cost, can't hallucinate |
| Progressive disclosure | claude-mem | recall mode=brief returns one-line refs (~45 tokens) before you pay for full context |
| Consolidation / dedupe | mcp-memory-service, Mem0 | Embedding-based duplicate detection on every write, plus maintain health reports; optional LLM merge that refuses lossy rewrites (dropped links or frontmatter) |
| Remote MCP for claude.ai | Supermemory, Mem0 | Self-hosted Streamable HTTP; your data never leaves your repo and your server |
Version 3.1 adds the best idea from each of nine other memory tools, read in their source and credited in docs/prior-art.md: tags, compaction steering and summary capture, session diffing, activity-aware decay, a code-aware tokenizer, errors in checkpoints, an honest status line, plugin packaging and alwaysLoad registration.
What else it does:
password: …, DB_PASSWORD=…, AWS_SECRET_ACCESS_KEY=…), connection strings with embedded passwords, card security codes, IBANs (mod-97 checked, spaces or hyphens), card numbers (Luhn checked, even with other digits beside them), Spanish DNI/NIE, French NIR (checksums), UK National Insurance numbers (written in capitals) and US SSNs *before* they become permanent git history. It reads through lookalike letters, other scripts' digits and zero-width characters, and plain prose such as "password: required", "tokens: 128000" or a Spanish date like "12/10/26" is left alone. It also catches opaque Authorization: Bearer/Basic headers, GitLab, Google OAuth, Slack and Discord webhook and bot tokens, Telegram, Twilio, Mailgun, Azure, Shopify, PyPI and DigitalOcean tokens, STRIPE_KEY=-style environment lines, PINs, and the quoted-JSON, markdown-bold and "the password is …" forms of a password. A secret that is base64-encoded, split across words or URL-encoded still gets through: it is a backstop, not DLP.maintain reports possible contradictions. Measured in docs/calibration.md. When each fact has a content word the other lacks ("dark" / "light", "weekly" / "monthly", "read" / "write"), they are never called duplicates either, because neither keyword overlap nor embeddings can tell a synonym from an opposite: the new fact is saved and flagged as a possible update, and maintain lists the pair as a possible contradiction. (Before this rule, half of a set of twelve such pairs were silently dropped in keyword mode.)When Claude Code compacts a long session, the conversation gets summarised and details die. githippo makes sure what matters doesn't.
flowchart LR
A[Context fills up] --> B[PreCompact hook] B -->|parse transcript, no LLM| C[checkpoint: goal, todos, files, where it stopped] C --> D[(local ~/.githippo)] C --> E[(repo sessions/)] F[Compaction] --> G[SessionStart hook, source=compact] D --> G G -->|injects the state itself, not a reminder to read it| H[Claude continues exactly where it stopped] I[MCP instructions + core memory] -.->|system prompt, never compacted| H
checkpoint with no args restores it.Bonus: a fresh session in the same project and branch within 24h gets a brief "last time you were…" note, including what changed in git since (commits, commits by others, branch switches, deleted files). The UserPromptSubmit hook proactively surfaces up to three relevant memories when the match is confident. It's capped at 300 tokens, skips trivial prompts and never repeats within a session. Words in your prompt that the vault has never seen count against a match, so an ordinary coding prompt that shares two generic words with a note ("refactor", "use") is not given memory: on 1,000 to 10,000 notes none of 20 unrelated coding prompts triggered an injection, while all 40 planted questions did, with the right note (test/report6-hook.test.js). Before compaction, githippo also tells the compactor what must survive, and after compaction it keeps the compactor's summary with the checkpoint.
How we know the hooks do what we say: the contracts were read from Claude Code's own code (2.1.258). PreCompact passes each successful hook's stdout to the compactor as custom instructions (Claude Code also shows that text in the transcript as "PreCompact … completed successfully"); PostCompact receives compact_summary; every hook receives session_id, transcript_path and cwd; SessionStart sources are startup, resume, clear, compact and fork.
Recall also learns what you actually use: memory that keeps being handed to Claude gets a small boost (at most +40% on its keyword score, +10% on its semantic score) that halves every 30 days without use. It is applied to those raw scores, so it only reorders results that were nearly tied: it can't push a clear match out of first place (an earlier version applied it after rank fusion and did, see test/report6-ranking.test.js). The counts stay on your machine, are kept per user, and with no usage data ranking is exactly the same as without it.
Wrap anything in … and it never reaches memory. An opening tag that is never closed makes everything after it private, and remember refuses the fact and tells you why, rather than silently keeping the part you meant to hide. Turn hooks off without editing files: GITHIPPO_HOOK_PROFILE=minimal or GITHIPPO_DISABLED_HOOKS=prompt,steer.
Retrieval, on a small labelled set (52 queries) and on LongMemEval-S (500 questions, retrieval only, no LLM):
| keyword + graph | + local model | |
|---|---|---|
| In-repo set: hit@5 | 64% | 100% |
| In-repo set: MRR | 0.60 | 0.89 |
| LongMemEval-S: R@5 | 96.2% (all 500) | 98.0% (100-question sample) |
Reproduce the first with githippo eval. Method, per-language breakdown, filing and duplicate accuracy, memory use and scale numbers are in docs/benchmarks.md. The set is small, hand-written by the author and in-domain: a regression guard and a rough guide, not a leaderboard.
Not measured yet, and it is the number that matters most: whether answers get better, or sessions cheaper, with githippo than without it. eval/qa.js and eval/behavior.js are built to measure exactly that and need an ANTHROPIC_API_KEY; they have not been run. Until they are, read "saves tokens" as: it adds a bounded cost to every turn (below) and pays that back only when a recalled fact replaces re-explaining or re-discovering something. If you run them, post the results in issue #3.
Nur der Anfang wird gezeigt; den Rest findest du im Repo