
Type Atlas
io.github.tyler-mitchell由 GitHub 帳號 tyler-mitchell 發布v1.0.0更新於 Oct 24, 2026
Editor-grade TypeScript, Markdown, and JSON intelligence for coding agents.
發布方自己的服務:Red Atlas Api
概覽
Type Atlas 為編碼助理提供編輯器級的 TypeScript、JavaScript、Markdown 與 JSON 智慧:語意導覽、診斷與程式碼搜尋。
- 可以做什麼
- 以樹狀列出檔案結構、行數與 git 狀態,並可一次讀取多個檔案,預設將函式內容摺疊為簽章。檢查符號的懸停資訊、定義、型別定義、實作、呼叫端、呼叫與參照,並找出哪些模組匯入了某個檔案。在已載入的專案中依名稱尋找宣告,或定位精確識別字及其語意參照。用自然語言描述行為來搜尋程式碼,追蹤相關程式碼,並跨工作區調查一個問題。在工作過程中依專案執行編譯器的全程式診斷。
- 適用情境
- 適合在 TypeScript 或 JavaScript 儲存庫中工作的助理,尤其是大型 monorepo,字串搜尋和整檔讀取往往給出不完整的樣貌。它旨在取代助理預設的程式碼導覽方式,並在日常工作中浮現型別錯誤,而不必另外執行型別檢查。
- 執行需求
- 透過 npx 從 npm 套件安裝,以 stdio 在本機執行;加入後需重新啟動用戶端。四個語意索引工具(search_code、related_code、investigate_code、search_dependency_code)需要安裝 uv。不繼承 shell PATH 的用戶端需要 npx 的絕對路徑,Windows 用戶端可能需要 cmd 加 /c。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Type Atlas,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
[Type Atlas — code intelligence for TypeScript]
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
Any other client takes the standard shape:
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
Response
inspect_symbol
Hover, definitions, type definitions, implementations, callers, calls, and references in one call. References are the residual after callers and definitions are accounted for, so a use is listed once. Against calling those tools separately it is 4x fewer characters and 7x fewer round trips.
Agent's Input
Response
read_file
The argument is an array, so several files arrive in one call. Bodies fold to
signatures by default and the header says how many lines that saved; fold: false returns them.
Agent's Input
Response
occurrences
Starts from an exact identifier when the agent knows its name but not its file. Identifier syntax nodes activate the relevant projects; TypeScript resolves canonical declarations and semantic references. Same-name symbols stay separate, overloads collapse, and unresolved identifiers are called out rather than mixed into the reference list.
Agent's Input
Response
search_code
Finds code by what it does, for when you cannot guess what it is called. Hits come back in rank order, each carrying the file range it came from, so the next call has somewhere to go. Live answers also carry a relevance percentage per hit; it is left out below because the embedding scores behind it differ between machines and these cases are compared byte for byte.
Agent's Input
Response
diagnostics
The compiler's own whole-program check, per project, not a per-file pass. An edit in one file usually breaks a different one, and this is the call that finds that file.
Agent's Input
Response
workspace_symbols
Find a declaration by name across every project the session has loaded, when you know roughly what it is called and nothing about where it lives.
Agent's Input
Response
file_references
Who imports this module. The module-level question, answered without picking a symbol inside it first.
Agent's Input
Response
Packages
Development
CONTRIBUTING.md has the change and release process.
來源:README.md,提交 9c06f9f
工具
0版本歷史
1- v1.0.0最新Sep 16, 2026
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