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Arbor

von Anandb71Version 1.0.0i★ –i–
Name in der Registryio.github.Anandb71/arbor

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Überblick

Beschreibung vom Entwickler (englisches Original)

The Graph-Native Intelligence Layer for Code.

Die drei Säulen von PopNx MCP

Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

  • Verbindung: –
  • Transport:
  • Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Bevor du installierst

  • Basischecks: 1 von 1 bestanden
  • Läuft auf deinem Computer mit den Rechten deines Benutzerkontos (Dateien, Netzwerk, Apps).
  • Die Registry nennt keinen Schlüssel zum Eintragen.

Der Entwickler hat in der Registry keine Installationsangaben gemacht. Sieh dir unten die README des Entwicklers an.

Was er kann

Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.

Basischecksi

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

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto Anandb71 bestätigt, dem das Repo gehört

  • … Noch nicht geprüft

    Wird noch gepflegt

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • … Noch nicht geprüft

    Hat eine Lizenz

    Dieses Repo haben wir noch nicht von GitHub gelesen

  • – Nicht zutreffend

    Endpunkt antwortet

    Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet

  • – Nicht zutreffend

    Anmeldung mit OAuth

    Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen

  • … Noch nicht geprüft

    Keine versteckten Anweisungen in Tool-Beschreibungen

    Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen

Im Vergleich mit anderen in Sonstigesi

  • Mehr Sterne als 0 % der anderen 32545 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 1 % der anderen 32545 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 32545 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Häufige Fragen

Ist Arbor sicher?

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.

Welche Schlüssel oder Codes braucht er?

Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.

Läuft er auf meinem Computer oder in der Cloud?

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).

Wird er noch gepflegt?

Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.0) kam vor 10 Monaten in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Python MCP

Alternativen

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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README vom Entwickler

README öffnen

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.

Code context for people and agents.

Find a function’s callers. Trace the path through your code.

Know what breaks before you break it.

arbor retirements finds direct OpenAI, Anthropic and Google SDK calls in Python code that use a retired or retiring model, and says what has to change.

OpenAI shuts down the dated gpt-4o and gpt-4.1 snapshots on 14 January 2027. Shutdown list

Simulated replay — the arbor commands and their output are real (tokio @ 178k LOC). Methodology: BENCHMARKS.md

v3.1.1 · A fix release. The arbor retirements data was read again on 28 October 2026 and now lists the bare gpt-5 and o3, which OpenAI's deprecations page gives 11 December 2026. npx @anandb71/arbor-cli runs on npm 12, and Arbor no longer takes your home folder as the project because ~/.arbor exists. Release notes


Why Arbor

Most AI coding tools treat code as text. Arbor builds a semantic dependency graph — functions, classes, and modules as nodes; calls, imports, and inheritance as edges — then answers execution-aware questions with deterministic precision:

QuestionArbor answer
*If I change this symbol, what breaks?*Blast radius with depth, confidence, and risk level
*Who calls this — directly and transitively?*Caller/callee traversal on the call graph
*What's the shortest path between A and B?*A* path through real dependencies
*Is this PR too risky to merge?*CI gate on blast-radius thresholds

No keyword guessing. No embedding hallucinations. One graph, every interface.

Where the graph is *unsure*, it says so — edges carry a confidence, and ambiguous resolutions are labelled rather than hidden. An honest unknown beats a confident wrong answer.


What's new in v3.1.1

A fix release. No breaking changes; as after every upgrade, a saved graph is rebuilt once on first use.

FixWhat was wrong
Bare `gpt-5` and `o3`OpenAI's deprecations page started listing bare IDs next to the dated snapshots after 3.1.0 was built, so model="gpt-5" or model="o3" was not listed at all. Both are listed now (11 December 2026, to GPT-5.6), with the 13 other IDs the page added.
Data read again on 28 October 2026Every provider page behind the bundled data was read and checked again. OpenAI's deprecations page lists the five dated gpt-4o, gpt-4o-mini, gpt-4.1 and gpt-4.1-mini snapshots for 14 January 2027; for the bare aliases the report now cites OpenAI's API reference ("Deprecated. Announced shutdown date: 2027-01-14") and its models API. A call moving to claude-haiku-4-5-20251001 with temperature now gets a check line: Anthropic's API version 2026-10-21 rejects it on every model.
`(no change)` next to arguments that need reasoning offFor a call whose client Arbor could not resolve, temperature, tools or max_tokens went unchecked and "let the model reason" read (no change). They are checked now. When Arbor cannot read some of a call's arguments (**kwargs, extra_body) or a check line names one of them, each option says so instead of no change.
`npx` on npm 12npm 12 skips install scripts, so the binary was never downloaded. The wrapper now downloads it on first run and checks it against the release's SHA256SUMS.
The home folder as the project~/.arbor holds the global config (and, on Windows, the installed binary), so a folder under home with no nearer project marker resolved to the whole home folder, and arbor index . indexed all of it. The search now stops at the home folder.
Code graph: aliased imports and bare callsAfter from m import f as g, a call to g() now reaches f (also for import { f as g } in TypeScript and JavaScript). In Python, JavaScript, TypeScript and Go, a bare call to a function in another file counts only when the calling file can see it (in Python, when it imports the name); other languages are unchanged.

When the terminal report of arbor retirements lists a call to a retired or retiring model, it now ends with an offer of a paid readiness review. The link carries three values from the run: how many calls are listed, how many are already retired and the next shutdown date. Arbor sends nothing. The offer is not printed with --json, --markdown, --annotations or --quiet, or when the CI environment variable is set (GitHub Actions sets it), and the GitHub Action does not show it. Release notes

v3.1.0 ( arbor retirements and arbor usages )

Two commands for Python code that calls AI model APIs. Both run locally, with no account, API key or telemetry.

NewWhat it does
`arbor retirements`Lists the direct openai, anthropic and Google SDK calls that use a model its provider has retired or is retiring: the date, the replacement the provider lists, the arguments that change with it and the choices your repo makes first. OpenAI's deprecations page lists the dated gpt-4o, gpt-4o-mini, gpt-4.1 and gpt-4.1-mini snapshots for shutdown on 14 January 2027; OpenAI's API reference and models API give the bare aliases the same date. More below
GitHub Action `mode: retirements`The same check in CI: a job summary of the affected calls it finds, and warnings on the most urgent lines. It warns by default and fails the build only when you set retirements-fail-on, or when the check cannot run.
`arbor usages` and `find_api_usages`The OpenAI, Anthropic and Gemini SDK calls Arbor finds, with their file and line, client routing (direct, Azure, custom base_url, Bedrock, Vertex) and model IDs, for people and agents. A value is confirmed only inside a small supported grammar; everything else carries a typed gap. What a report confirms

Python only for now. Release notes

v3.0.3 (Rust calls through paths and macros, per-symbol diff, --base )

A fix release. Every item below was a wrong answer, not a missing feature, and each ships with a regression test.

FixWhat was wrong
Rust calls resolvecrate::jobs::enqueue(), Type::new(), self.helper() and calls inside assert!/format! produced no edge, so heavily used Rust functions reported no callers. Paths now resolve through the module tree, and macro arguments are read as code.
Per-symbol `arbor diff`Every symbol in a touched file counted as changed, so adding a function to a busy file reported that file's whole blast radius. New symbols now carry none; only modified ones do. Tests that call the change are listed as worth running, not counted as impact.
`--base` and `--staged`arbor diff, check and summary saw only uncommitted edits unless ARBOR_DIFF_BASE was set. --base origin/main compares against the merge base, which is what a pull request shows; --staged checks just what is staged.
Languages stay apartA TypeScript enqueue could be reported as a caller of a Rust enqueue. Resolution stays within a language family, and callers/callees list each same-named definition separately.
No stale graphsAfter a branch switch, answers came from the old branch's graph when no remaining file was newer than it. The graph now records the commit it was built from and refreshes when HEAD moves.
Inheritance edgesclass Middle(Base) produced no edge, so changing a base class showed zero blast radius. extends/implements edges are emitted and inherited methods stay reachable.
Call cycles rank as oneA closed ring of functions filled the top of every centrality ranking. Cycles are condensed before PageRank.
HTTP bridge hardeningarbor bridge --http accepted cross-origin and DNS-rebinding requests. It now checks Origin/Host and requires JSON bodies.
Quieter bridgeThe bridge re-indexed ignored build directories in a busy loop.

Also new: arbor receipt. After each coding-agent turn it explains, in plain English, what changed and what was touched that you didn't ask for, with arbor receipt undo to put a turn back.

Cached graphs from 3.0.0 are rebuilt automatically on first use.

v3.0.0 — The Right Node (symbol resolution consults the importing file)

One fix, measured.

Symbol resolution consults the importing file. When a bare name matched definitions in several modules, resolve_ref fell through to SameDir and attached the edge to whichever definition sat in the caller's own directory — not a dropped edge, a confidently misrouted one, stamped at 0.55 confidence.

GraphBuilder already kept a per-file import map, but only apply_import_validation read it, and that scores an edge *after* one has been chosen. It never saw the references going to the wrong node. Consulting it between the same-file and same-directory checks keeps a local definition shadowing an import, while letting a written import beat mere adjacency. Resolution::ViaImport scores 0.93, above SameDir's 0.55.

Measured

A fixture of 260 modules across 10 layers, each layer defining the same 26 function names. Ground truth is derived from the generator's own edge list, so the expected answer is exact rather than estimated.

True downstreamv2.6.0v3.0.0
1790163
1780161
1610133
14322133
12222119
362261
162246

Previously flat at about 22 regardless of the real answer. Now it tracks. Risk on the largest hub moves from LOW to CRITICAL.

Total edge count barely moves (1335 → 1334). That is the signature of misrouting rather than loss: the edges were always there, pointing at the wrong nodes.

Breaking
  • Resolution gains a ViaImport variant — an exha

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