
What's Loaded
io.github.stcmain由 GitHub 账号 stcmain 发布v0.2.5更新于 Oct 24, 2026
What fills your agent's context window before a session starts: skill descriptions, memory files.
概览
一个本地 MCP 服务器,用于报告 AI 代理在会话开始前上下文窗口里已加载的内容,并按估算 token 成本排序。
- 可以做什么
- 报告上下文预算总量并按来源拆分,作为排查的起点。按 token 成本对已安装技能排序,便于优先精简最贵的部分。找出重复安装的技能,并区分内容完全相同的副本与同名但内容不同的技能。统计 CLAUDE.md、AGENTS.md 等记忆文件的大小,以及其导入行额外引入的内容。列出各受支持客户端中配置的所有 MCP 服务器及其所在的配置文件。
- 适用场景
- 当会话比以前更早触发压缩,或安装了大量技能、插件和记忆文件、想弄清哪些最占上下文时适用。也适合审计 Claude Desktop、Cursor、Windsurf 和 VS Code 中配置了哪些 MCP 服务器。
- 运行要求
- 以 stdio 方式在本地运行,通常通过 npx 或打包好的桌面扩展安装。npm 方式需要 Node.js,桌面安装包自带依赖。无需凭据或 API 密钥。有一个可选设置 WL_PROJECT_ROOT,用于指定被视为项目的目录。会读取主目录下的 Claude Code 目录结构以及 JSON 格式的客户端配置。
安装
在 SourceWeft 中
- 打开 控制台中的 What's Loaded,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
whats-loaded-mcp
[npm] [License: MIT] [stcmain/whats-loaded-mcp MCP server]
Your context window is already half spent before you type. An MCP server that shows what is consuming it — every skill description, every memory file and its hidden @imports, every configured MCP server — ranked by cost, with duplicates called out.
Why
Skills are cheap to install and permanently expensive to keep. A skill's name and description go into the system prompt of every session, forever — only the body is loaded on demand. Install a few hundred and you've quietly mortgaged half your window before the first message.
Nothing surfaces this. You notice it as sessions that compact sooner than they used to, and you have no idea which of the things you installed six months ago is responsible.
On the machine this was written on:
79 names were installed more than once — the same skill picked up from several sources, like agent-browser appearing three times from three authors. But a shared name does not always mean a redundant copy: on that install only 34 groups were byte-identical (~1,523 tokens genuinely recoverable), while 45 shared a name and differed in content — different work wearing the same label, where deleting a copy loses something. duplicate_skills compares content hashes and reports those two groups separately, so the cleanup advice is safe to act on rather than merely impressive.
Tools
Install
Claude Desktop (one-click, no terminal): download the latest whats-loaded-mcp-<version>.dxt from Releases and open it with Claude Desktop (double-click, or Settings → Extensions → Install Extension…). The server and its dependencies ship inside the bundle — no npm, no Node install.
Register with Claude Code (available in every session):
Or in any MCP client config:
From source
Published as whats-loaded-mcp on npm and as
io.github.stcmain/whats-loaded-mcp in the MCP Registry.
Configuration
One optional setting, and it takes no credentials.
Personal and plugin scopes are read from ~/.claude either way. Setting this is
worth it when a desktop client launches the server: the process inherits that
client's working directory, which is rarely the project you are asking about.
What it counts, and what it refuses to guess
Getting this wrong in the flattering direction would be easy, so the accounting is deliberately conservative:
- Skill descriptions only.
name+descriptionis what loads at startup. The body of aSKILL.mdis fetched on demand and is not counted, even though it is 100× larger. - Enabled plugins only. Skills belonging to disabled plugins sit on disk costing nothing, and are reported separately rather than folded into the total.
- One version per plugin. The plugin cache keeps several content-hash copies of the same plugin; only the live one is counted. Counting them all would inflate the total and invent duplicates you cannot act on.
marketplaces/is never counted. That tree is a git checkout of marketplace source, not installed content.
Honest limitations
- Token counts are estimates (~4 chars/token). Real counts depend on the tokenizer; prose runs lighter, code and CJK run denser. Treat the numbers as a ranking and a rough scale, not as billing. Anthropic's tokenizer is not public, so nothing local can do better than an estimate.
- MCP tool definitions are not measured. They can be a large share of your context, but measuring them means launching every server and enumerating its tools. This server does not launch anything, so it reports the server count and says so rather than guessing.
- JSON configs only. TOML-based clients (Codex
config.toml) are not parsed. - Client-specific. Built around the Claude Code layout (
~/.claude). The MCP inventory reads Claude Desktop, Cursor, Windsurf and VS Code configs too, but skill accounting is Claude Code's model. - It reports; it does not edit. Nothing is deleted, disabled or rewritten. Acting on the findings is your call.
Design notes / threat model
This server's output goes straight into a model's context, so the interesting risk is not what it does to your machine — it is what it hands to the model.
- No child processes. No network. It only reads files. There is no
exec, no shell, and no outbound connection anywhere in the codebase. - No model input ever becomes a path. Every path is derived from
homedir()orcwd(). The only model-controlled parameters are a clamped integer and a substring matched in memory against names already collected. Path traversal is not possible because there is no path construction to traverse. - Memory file contents are never read into the report.
CLAUDE.mdroutinely contains private operational detail. This server reports size and the import graph, never a line of content. - MCP environment values are never read. Config files are where people leave API keys in plaintext. Only variable names are emitted — never values, not even masked.
- Skill names and descriptions are emitted, which is a deliberate exception: they are already in the model's context by definition, so reporting them discloses nothing new.
- Bounded work: depth-capped directory walks, symlink-loop protection via realpath, and a file size ceiling.
Who makes this
Built by Shift The Culture — we run a one-person company on AI agents and ship the tooling we needed ourselves. This server is free and MIT-licensed, no strings.
It has three siblings, all also free and MIT:
- whats-running-mcp — what is actually running on the box right now, instead of what an old transcript claims.
- whats-inherited-mcp — what a checkout you did not write tells your agent to do: instruction files, hooks, and the MCP servers it declares.
- whats-allowed-mcp — what your agent can do without asking you: merged permission rules, which settings file wins, and the rules your client accepts and then ignores.
The rest of that tooling is paid:
- Agent Fleet Ops Kit ($29) — the other failure modes of running three or four agents on one box: two sessions editing the same checkout, a dev server nobody owns (so the agent tests a different app than it edits), and MCP servers leaked from crashed sessions that hold ports and RAM for weeks. Prefer PayPal? Same kit on Payhip.
- Agent Reliability Kit ($29) — a Stop hook and two CLIs that block a turn when an agent claims "done" against a repo, URL, or build that was never actually checked. Prefer PayPal? Same kit on Payhip.
The server above stays free and MIT either way — it has no upsell in it, no telemetry, and no dependency on the paid kits.
Sponsors
This server is MIT and stays MIT. There is no pro edition, no telemetry, and nothing held back from the free build. Sponsorship is how the maintenance gets paid for without any of that changing.
No sponsors yet — the first slot is open. Company sponsors get their name or logo in this section, in the two sibling servers, and on the sponsor page. Tiers, exactly what the placement is, and what it explicitly does not buy: https://shifttheculture.media/sponsor
Individuals: https://paypal.me/ShiftTheCultureLLC — any amount, no perks, no tier.
License
MIT © Zachary Pampu
来源:README.md,提交 7342b8a
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0版本历史
1- v0.2.5最新Sep 16, 2026
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