Prototyp · Vorschau: alle Server aus der offiziellen Registry, alle 30 Minuten synchronisiert. Bewertungen und Benutzerkonten folgen in einem späteren Schritt.
PopNx MCPMCP-Server für alle, die KI nutzen · in einfachen Worten erklärt

Type Atlas

von tyler-mitchellVersion 1.0.0i★ –iLäuft auf deinem Computer
Name in der Registryio.github.tyler-mitchell/type-atlas

Installieren

Überblick

Beschreibung vom Entwickler (englisches Original)

Editor-grade TypeScript, Markdown, and JSON intelligence for coding agents.

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: Läuft auf deinem Computer
  • Transport: stdio
  • 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.

Du brauchst

  • npmNode.js installiert (für den Befehl npx)

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": {
    "type-atlas": {
      "command": "npx",
      "args": [
        "-y",
        "@type-atlas/mcp"
      ]
    }
  }
}

Führe das in deinem Terminal aus

claude mcp add type-atlas -- npx -y @type-atlas/mcp

In Cursor öffnen

Oder kopier die Einstellungen selbst

In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen

{
  "mcpServers": {
    "type-atlas": {
      "command": "npx",
      "args": [
        "-y",
        "@type-atlas/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 VS Code öffnen

Oder kopier die Einstellungen selbst

In .vscode/mcp.json in deinem Projekt einfügen

{
  "servers": {
    "type-atlas": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@type-atlas/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.

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 6. Nov. 2026

  • ✓ Bestanden

    Entwickler passt zum Repo

    Der Registry-Name wurde mit dem GitHub-Konto tyler-mitchell 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 32531 Server in dieser Kategorie
  • Neuer in der Registry veröffentlicht als 31 % der anderen 32531 Server in dieser Kategorie
  • Basischecks gleich gut wie oder besser als bei 100 % der anderen 32531 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 Type Atlas 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 2 Monaten in die Registry.

Welche Apps können ihn nutzen?

Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.

Was kann ich stattdessen nutzen?

In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Reelsaw

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

Spec Driven Development

von formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Läuft auf deinem Computer★ 440MITAktualisiert vor 14 Monaten
Installieren

Remote Desktop Commander

von desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Läuft in der Cloud★ 211Aktualisiert gestern
Installieren

Reelsaw

von osbytes

Drive a self-hosted Reelsaw: turn long videos into vertical clips, edit, re-render and export them.

Läuft auf deinem ComputerAktualisiert heute
Installieren

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.

Type Atlas is what I have all my code agents use across all of my TypeScript projects for all code navigation needs. Most of those projects are monorepos. Some are large and complex enough that understanding how a change fits into the rest of the system is a real part of the work. This tool was designed as a complete replacement for an agent's default code navigation methodology.

I've been iterating on this tool for months based on how my own coding agents actually work in my projects. Most of what Type Atlas does, exists because I kept seeing the same problems:

  • Agents reason from an incomplete view of the system. They may understand the file they found while missing the surrounding code that determines how it is supposed to be used.
  • Agents rebuild things that already exist. The capability is already in the repo, but the agent never finds it because it does not know what it is called.
  • Agents often read either too little code (Claude) or far too much (Codex). Too little leaves them making decisions without enough surrounding context. Too much fills the context window with entire files and implementation detail that never mattered to the task.
  • Agents repeatedly stop to run type checks just to find errors an IDE would already be showing. That adds latency throughout implementation and pushes feedback later than it needs to arrive.
  • Agents are fundamentally operating blind. String-search navigation never gives them a strong internal atlas of the codebase. They are forced to make implementation decisions from fragments of files and matches they happened to retrieve, with important structure and compiler-known information still missing.

As projects grow, these problems compound and start showing up directly in the quality of the code agents write.

Semantic code navigation

Coding agents navigate code through file reads and string searches by default. That gives them source text and leaves the model to reconstruct relationships that the TypeScript language service already knows.

Type Atlas gives the agent direct access to that semantic information:

  • A symbol resolves to its actual definition and references rather than every occurrence of the same text.
  • Callers and implementations are identified by their relationship to the symbol.
  • Inferred types come from the language service instead of being reconstructed from nearby source.
  • Results keep their source range and owning TypeScript project attached.

A text match is still useful when text is what the agent is looking for. It is a weak substitute for semantic navigation when the question is about the program itself.

Find what already exists

Large codebases contain useful code that an agent has no reason to know by name. String search works best after the agent already knows enough vocabulary to formulate the search.

Type Atlas gives it other ways in:

  • The agent can describe behavior in natural language and find code based on what it does.
  • A discovered result leads back to a real symbol and an exact source range.
  • From that symbol the agent can follow actual relationships through the codebase instead of guessing another identifier to search for.

This is especially useful in large monorepos. Existing helpers and established implementations are easier to discover before the agent decides it needs to create another one.

Diagnostics during normal work

A developer in an IDE sees compiler feedback while working. Coding agents usually get that feedback by stopping implementation to run a type-check command and then waiting for the result.

Type Atlas moves much of that feedback into work the agent was already doing:

  • Relevant diagnostics can arrive with normal code-intelligence responses.
  • Errors show up while the affected code is still part of the agent's current working context.
  • A bad type assumption can be caught before it turns into several dependent edits.

I still use full type checks for verification. They do not need to be the main way an agent learns about errors while it works.

Responses are built for model context

Making a response smaller is useful only when the information removed was unnecessary. Models also use the organization of what remains.

Type Atlas treats structure as part of the information:

  • Labels make the role of a result explicit.
  • Grouping keeps related facts together.
  • File boundaries stop unrelated source from blending together.
  • Source locations stay attached to the thing they describe.
  • Trees keep their hierarchy instead of becoming a flat sequence.
  • Diagnostics retain the source needed to understand them.

The same principle determines what gets omitted. Function bodies can stay folded when the signature is enough. Repeated serialization and unrelated source do not need to occupy the context window simply because they were available.

The goal is useful information density. Fewer tokens matter, but removing the structure that helps the model understand those tokens would defeat the point.

Information for the next decision

Every tool call is part of the agent's reasoning process. A good response should answer the current question while leaving the agent in a better position to decide what to inspect next.

Type Atlas keeps useful follow-up information close to the result that exposed it:

  • A symbol can arrive with the relationships needed to understand how it participates in the codebase.
  • Repository structure can carry line counts and working-tree state alongside the files themselves.
  • Search results include concrete source ranges that can be followed directly.
  • Project context remains attached as the agent moves from one result to another.

This gives the agent better evidence at each branch in its investigation. It can follow relationships that actually exist in the program instead of treating every textual match as an equally meaningful lead.

The benefit is higher-quality navigation. Each step preserves more of the information needed to choose the next one.

Project and scope awareness

TypeScript questions depend on project context. That becomes especially important in a monorepo, where an answer can be correct inside one project while still being incomplete for the repository as a whole.

Type Atlas keeps those boundaries visible:

  • Files are resolved through the TypeScript project that owns them.
  • Results state the project scope they came from when that scope matters.
  • Counts make the size of a result explicit.
  • Limits are stated when an answer covers less than the whole repository.
  • Source locations can be passed directly into later calls.

The agent gets enough information to understand what an answer actually covers before relying on it.

Built from daily agent use

I use Type Atlas with my own coding agents every day across all of my TypeScript projects. The current behavior came from repeated use.

A lot of the design can be traced directly to recurring agent behavior:

  • Reads fold because agents were spending context on bodies they did not need.
  • Diagnostics travel with normal responses because repeated type-check commands were wasting implementation time.
  • Semantic relationships are grouped because agents kept reconstructing the same information through separate calls.
  • Natural-language code search exists because useful code often has a name the agent could never infer from the task.

That is still how I work on Type Atlas. When I keep seeing agents waste time on the same navigation problem or repeatedly miss the same kind of information, I change the tool.

The examples below are captured from the running server against a fixture monorepo and regression-checked with the implementation.

Install

codex mcp add type-atlas -- npx --yes @type-atlas/mcp@latest

claude mcp add --scope user type-atlas -- npx --yes @type-atlas/mcp@latest

code --add-mcp '{"name":"type-atlas","command":"npx","args":["--yes","@type-atlas/mcp@latest"]}'

Any other client takes the standard shape:

{

"mcpServers": { "type-atlas": { "command": "npx", "args": ["--yes", "@type-atlas/mcp@latest"] } } }

A client that starts servers without your shell PATH will not find npx by name; give the absolute path from which npx when that happens. On Windows, a client that cannot launch the npx.cmd shim needs "command": "cmd" with "args": ["/c", "npx", "--yes", "@type-atlas/mcp@latest"].

Clients read MCP config at startup, so restart after. @latest resolves on every process start; pin a version if you do not want tool behavior moving under you.

search_code, related_code, investigate_code, and search_dependency_code run a semantic index through uvx and need uv. Without it those four report that uv is missing, explore_symbol drops its related-code section, and the rest is unaffected.

Recommended

Installing the server does not change what an agent reaches for. Some agents, Claude among them, will assemble whatever their shell allows, chained together, and produce a fresh justification each time, so naming a few commands to avoid does not hold. The instruction has to rule out the whole category and name the exceptions. Add this to AGENTS.md or CLAUDE.md:

Type Atlas MCP is the required tool for reading and navigating code in

TypeScript and JavaScript. This is not a preference. No shell command is an

acceptable substitute, whatever it is composed of, and neither is a plain

file read. The only valid fallbacks are a server that is down, a call that

errored, or a file that is neither TS nor JS.

--require-intent

This opt-in flag requires one decision sentence for broad exploration tools such as repository search and workspace symbols. Targeted reads and semantic lookups stay unaffected, and intent is never echoed into tool responses.

Tool call results

Paths are workspace-relative, coordinates are one-based, so a location in one answer is valid input to the next call. Editing tools return patches; nothing is written for you.

Everything below is captured from the running server against fixtures/ledger by the scenario suite, which replays the same calls and fails on drift. Nothing here is hand-written, and changing what a tool answers changes this file in the same commit. The source is README.mdoc. Every tool has a page with more cases in docs/tools.

list_files

Structure, line counts, and git status in one tree, using the badge letters editors already use. Deleted files get a row even though they exist only in git's answer. Folded directories say what they hold rather than disappearing.

Agent's Input

tool: List files

workspace: fixtures/ledger

working tree arranged: currency.ts edited · rounding.ts created · index.ts deleted

directory: packages/money depth: 2

answered in 57ms

Response

packages/money/

├ src/ · 3 changed │ ├ currency.ts · 21 loc · M +2 │ ├ index.ts · D -12 │ ├ money.ts · 58 loc │ ├ rounding-mode.ts · 15 loc │ └ rounding.ts · 11 loc · U ├ tests/ │ ├ money.test.ts · 15 loc │ └ rounding-parity.ts · 15 loc ├ package.json · 19 loc └ ts

Nur der Anfang wird gezeigt; den Rest findest du im Repo

PopNx fragen