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Type Atlas

作者:tyler-mitchell版本 1.0.0i★ –i在你的电脑上运行
注册名称io.github.tyler-mitchell/type-atlas

安装

概览

作者提供的说明(英文原文)

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

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

在终端中运行这条命令

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

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 tyler-mitchell 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32678 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32678 个服务器的 31% 更新
  • 基础检查结果等于或优于此分类中其他 32678 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Type Atlas 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.0.0)于2个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Starreel

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

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

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

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

在云端运行★ 211前天更新
安装

Starreel

作者:starreel

Turn a script into a finished, downloadable short-drama episode — via MCP or REST.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

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