GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Beschreibung vom Entwickler (englisches Original)
Agent context flight recorder: restore after compaction, fan-out packs, signed git-bound receipts.
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": {
"lossless-context": {
"command": "npx",
"args": [
"-y",
"lossless-context-mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add lossless-context -- npx -y lossless-context-mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"lossless-context": {
"command": "npx",
"args": [
"-y",
"lossless-context-mcp"
]
}
}
}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": {
"lossless-context": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"lossless-context-mcp"
]
}
}
}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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto NORTHTEKDevs 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 (2.0.0) kam vor 3 Monaten 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: GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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.
The flight recorder for your agent's context. A persistent, hook-fed ledger of every file version your coding agent was shown — so a compaction can't destroy the working set, a subagent fleet doesn't pay for the same files N times, and you can *prove* afterward exactly what the model saw.
┌──────────────────────┐
ledger reads ──────▶│ │──▶ RESTORE working set survives /compact (read_file, MCP) │ flight recorder │──▶ PACKS one cache-cached prefix for a fan-out fleet transcript sweeps ─▶│ (content-addressed │──▶ RECEIPTS signed, git-bound "what did it see" (native Read/Edit) │ archive on disk) │──▶ METERING where the read tokens went, in dollars └──────────────────────┘
Compaction destroys your agent's working set. Not anymore — sweep at PreCompact, manifest injected after, blind edit *blocked*, working set restored, edit allowed:
Two agents, one file — air traffic control. The second agent is stopped mid-clobber, with the culprit named:
Every line in these recordings is genuine output from the shipped code — the demos are generated by docs/demo/make-demo.mjs, which drives the real hooks and server and renders what they actually said. Re-run it yourself.
When Claude Code compacts, roughly two-thirds of a typical context is tool output — mostly file contents — and compaction discards it permanently. The model then flails: re-reading files it half-remembers, or worse, guessing at contents it no longer has (#27242 is the ask, at 80 👍).
The flight recorder closes the loop automatically:
Read/Edit/Write included, not just MCP reads), then writes a ranked working-set manifest. Fast enough to sit on the compaction path — one real 14 MB transcript swept in 361 ms; measure yours: node bench/sweep-bench.mjs .Cross-*session* memory tools (claude-mem and friends) summarize what happened for the next session. This is the complementary, mid-session layer: file-version-exact recovery of what you were just working on.
The recorder knows exactly which file versions the model has actually seen this context epoch. A PreToolUse hook uses that to stop the two ugliest edit failures *before the write lands*:
Fail-open by construction: any doubt (unparseable transcript, partial reads, files the model itself just edited, oversized files) → the edit proceeds untouched. Disable anytime with LOSSLESS_GUARD=off.
Run two agent sessions on one repo and they clobber each other blind: B edits a file A read ten minutes ago; A edits from its stale copy; the merge is garbage and neither notices. Nothing on the market mediates this locally — but the recorder already knows, per session, what each agent holds and edits. v2 makes that knowledge active:
~/.lossless-context/presence/, one file per process, no daemon, no locks). Another agent editing the same file seconds later is denied with the culprit named: *"agent session 3f2a91b0 started an edit on this file 12s ago and it may not have landed yet."* Covers sibling subagents of the same session too.coordination_status shows every visible agent session, what it's been editing, and which files have cross-session or in-flight activity.Honest limits: advisory, not locking. Sessions without the hooks are invisible, a same-second race can still slip through, and presence files are unauthenticated local JSON — any local process could fabricate one to cause false *denies* (structurally never a false allow; presence can only add deny classes). An intent whose edit is then declined at the permission prompt lingers up to LOSSLESS_COORD_INTENT_SECS (90 s) before expiring. It substantially narrows the concurrent-clobber window; it cannot close it, and how much it catches in practice is not yet measured. LOSSLESS_COORD=off disables coordination independently of the guard. (The guard's compaction tracking is session-scoped; only the dedup engine uses the machine-global epoch file, where a cross-session bump merely costs one conservative full re-send.)
Fan-outs are where token waste actually lives. Measured across 195 real multi-agent runs: 19.6% of all subagent `Read` tokens were duplicate reads of identical content by sibling agents (5.18M of 26.4M tokens) — every sibling starts cold and reads the same CLAUDE.md, the same spec, the same core modules.
export_pack ranks the archive's cross-session read history for stable hot files and renders them as one deterministic block for a custom agent-type's system prompt. The block is a stable prefix, so the whole fleet hits the provider prompt cache on it. On a real review fan-out this measured 46.55% cheaper than baseline — and the same pack injected per-task measured 19.6% *worse* (every sibling cache-writes it), which is why the tool tells you where to put it. Both numbers were measured externally on one real corpus, not by a harness in this repo — exact figures, method, and that caveat are in BENCHMARK.md. Generate the pack once per run and embed it verbatim: ranking follows live read history, so repeated export_pack calls can differ.
context_blame (also a CLI: lossless-context-mcp blame ) answers the debugging question every agent incident report wishes it could: for a given file, every content version the model was shown (SHA-256 + git blob SHA-1, first/last seen, capture source, sessions) and what else was in context around a chosen moment. When an agent produces a wrong change, you query the recording instead of arguing with the agent's self-report.
Observability vendors capture what your agent read into mutable trace stores. Nobody signs it or binds it to repo identity — and agent self-reports are not evidence (ask anyone whose agent claimed it "verified" something it never read).
context_receipt issues an HMAC-SHA256-signed attestation: every file/view shown, the SHA-256 of every content version, the git blob SHA-1 of each version (so any verifier with a clone can check git cat-file -e — was this ever committed?), repo HEAD at issue time, delivery kinds, token totals, and an explicit coverage statement of which capture paths it attests (mcp, and transcript-sweep with include_sweep). By default it signs with the same key file as trust-mcp receipts, so one key verifies a full evidence chain: *what the agent saw + what it did*.
The honest scope: a receipt attests what passed through the ledger and sweeps — it never claims coverage of unmediated paths, and says so in its own coverage.note.
context_stats shows where the session's file-read tokens went — per repo, per file, in dollars, counted with a real tokenizer.
Reality check, kept from earlier versions because it's true: as an intra-session
token saver this measures ~0% on real Claude Code transcripts (+0.4% with the
never-lose engine; the native file-state cache already ate the opportunity — full data
in BENCHMARK.md). The savings that DO exist are cross-agent (packs,
above). Read-path dedup remains because it is provably lossless and never negative —
not because it will save you much on its own.
npm i -g lossless-context-mcp
lossless-context-mcp init # wires all hooks into ~/.claude/settings.json claude mcp add lossless-context --scope user -- lossless-context-mcp
init is idempotent (re-run it after upgrades — it updates paths instead of duplicating), backs up your settings file first, refuses to touch a settings file it can't parse, and never removes hooks that aren't its own. --dry-run previews. It wires:
sweep-transcript.mjs (PreCompact + SessionEnd) — captures the working set + exact versions; bumps the dedup epoch on PreCompact; never blocks compaction.inject-manifest.mjs (SessionStart, matcher compact) — injects the recovered working-set manifest after a compaction.reset-epoch.mjs (SessionStart) — keeps read dedup lossless across new sessions.guard-edit.mjs (PreToolUse, Edit|Write|MultiEdit) — the blind-edit guard (LOSSLESS_GUARD=off disables without unwiring).Restart Claude Code after init. Without the hooks everything still works — you just lose automatic native-tool capture, post-compaction injection, and the guard; the ledger then records MCP reads only.
| Tool | What it does |
|---|---|
read_file(path, symbol?, lines?, force_full?) | Lossless read: full / unchanged-marker / diff. Optional single-symbol or lines:"40-90" views. Refuses binary files. |
read_files(paths[], force_full?) | A working set in one call; per-file errors don't fail the batch. |
working_set(limit?) | Heat-ranked table of what the recorder knows this session (+ last 24h), with staleness vs disk. |
restore_context(files?, budget_tokens?) | Re-emit the working set after compaction — manifest top-K by default, budget-capped, change-annotated. |
export_pack(repo?, top?, budget_tokens?, days?) | Deterministic fan-out context pack from cross-session read history, for an agent-type system prompt. |
context_blame(path, at?, window_minutes?) | Forensics: every version of a file the model was shown, plus co-context around a moment. Also: lossless-context-mcp blame from the shell. |
coordination_status() | The radar: visible agent sessions, their recent edits, cross-session and in-flight files. |
outline(path) | Cheap structural map of a file (declarations only). |
| context_stats() | Token/dollar b
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