原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Fitter

作者:PxyUp版本 1.8.3i★ –i在你的电脑上运行
注册名称io.github.PxyUp/fitter

安装

概览

作者提供的说明(英文原文)

Turn any website or API into structured JSON with LLM-authored declarative scraping configs.

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: 网页与浏览器

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

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 …”。

下载作者的 .mcpb 文件

链接指向作者自己的文件;我们不托管也不重新打包它。打开文件后,Claude Desktop 会进行安装。

在终端中运行这条命令

claude mcp add fitter --env FITTER_PLUGINS=your-value -- docker run -i --rm -e FITTER_PLUGINS ghcr.io/pxyup/fitter-mcp:v1.8.3

运行前请先填写空着的值。

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": {
    "fitter": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "FITTER_PLUGINS",
        "ghcr.io/pxyup/fitter-mcp:v1.8.3"
      ],
      "env": {
        "FITTER_PLUGINS": "your-value"
      }
    }
  }
}

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": {
    "fitter": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "FITTER_PLUGINS",
        "ghcr.io/pxyup/fitter-mcp:v1.8.3"
      ],
      "env": {
        "FITTER_PLUGINS": "your-value"
      }
    }
  }
}

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。

需要你填写的值

  • FITTER_PLUGINS env
    Optional path to a fitter plugins folder

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8日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 PxyUp 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“网页与浏览器”中的其他服务器比较i

  • 星标数多于此分类中其他 1381 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1381 个服务器的 26% 更新
  • 基础检查结果等于或优于此分类中其他 1381 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

Fitter 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(1.8.3)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 MCPB, Docker。

有什么可以替代它?

同一分类中有:Browser Use, Chrome DevTools MCP, MCP Server Browser

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:↓ 每周下载量i★ 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

Browser Use

Browser agents and stealth cloud browsers for AI: run web tasks, fill forms, extract data.

作者:browser-use广泛使用↓ 155.2万/周★ 12万18天前更新

电脑或云端✓ browser-use.com

Chrome DevTools MCP

MCP server for Chrome DevTools

作者:ChromeDevTools广泛使用↓ 188.4万/周★ 5.5万17天前更新

在你的电脑上运行

MCP Server Browser

MCP server for browser use access

作者:bytedance广泛使用↓ 792/周★ 4万14个月前更新

在你的电脑上运行

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。

Fitter — web data for AI agents

Fitter turns any website or API into structured JSON — declaratively. One JSON/YAML config describes where the data lives (HTTP request, headless browser, file, static value) and what to extract (JSON paths, CSS selectors, XPath). No code, no brittle scraping scripts.

🚀 [Try it in your browser](https://pxyup.github.io/fitter/) — the real engine compiled to WebAssembly: live examples, a visual config builder, no install.

Because configs are plain data, LLMs can author them. The built-in MCP server lets Claude Code, Claude Desktop, or any MCP client write and run scraping pipelines on your machine, on demand:

*"Get the top 5 HackerNews stories with titles and scores"* → the model authors a fitter config, validates it, runs it locally, and gets clean JSON back.

One engine, five ways to use it:

🤖 Fitter MCPMCP server exposing fitter to Claude Code, Claude Desktop and any MCP client
🧠 Fitter AgentAI-powered CLI: natural language → config → executed result
🖥 Fitter CLIrun configs locally for test/debug/home usage
📦 Fitter Libembed the engine in your own Go program
⚙️ Fitterlong-running service mode with scheduling & notifications

Why fitter for AI agents?

  • Declarative & auditable — the agent produces a config you can read, save and re-run, not throwaway code
  • Local-first — all fetching happens on your machine; no third-party scraping API, no keys, no per-request billing
  • Batteries included — HTTP client, headless browser (Playwright/Chromium/Docker), JSON/HTML/XML/XPath/PDF parsing, pagination, cached references, host rate-limits — in a single static binary
  • Reusable — what the agent authored today becomes tomorrow's cron job or service config

How to use Fitter_MCP

Fitter MCP is a Model Context Protocol server (stdio transport) which lets any MCP client — Claude Code, Claude Desktop, IDE assistants, custom agents — run Fitter configs and get structured JSON back.

Quick start (Claude Desktop — one click)

Download fitter-mcp- - .mcpb from the release page and open it — Claude Desktop installs the server automatically.

Quick start (Claude Code)
# 1. get the binary: download fitter_mcp_<version>-<os>-<arch> from the release page

https://github.com/PxyUp/fitter/releases — or build it from source:

go build -o fitter_mcp ./cmd/mcp

2. register it once, available in every project

claude mcp add fitter -s user -- "$(pwd)/fitter_mcp"

Then just ask:

*Get the top 5 HackerNews stories with titles and scores using fitter*

The model calls fitter_config_reference, authors a config, optionally checks it with fitter_validate_config and executes it via fitter_run — all data fetching happens locally on your machine. For a ready-made pipeline try examples/config_morning_briefing.json:

*Run examples/config_morning_briefing.json with fitter and give me the briefing*

Register in Claude Desktop
{

"mcpServers": { "fitter": { "command": "/path/to/fitter_mcp" } } }

Browser support (Playwright)

The .mcpb bundle and native binary ship without browsers: HTTP, static and file connectors work out of the box, but browser configs (the playwright connector) need Playwright's browsers. A few ways to get them:

  • On first use (native binary / `.mcpb`): set "install": true in the playwright connector — fitter downloads the driver + browser matching its built-in playwright-go version on first use (one-time, cached), so no separate install step is needed.
  • Ahead of time (native, optional): to avoid the first-run download, install the browsers beforehand with the same playwright-go version fitter is built against (check go.mod, currently v0.6100.0):
  go run github.com/mxschmitt/playwright-go/cmd/playwright@v0.6100.0 install

Linux: append --with-deps to also install the required OS libraries

  The version must match `go.mod` exactly — `playwright-go` refuses to run against a mismatched driver. Then run configs without `"install": true`.
  • Docker: use the ghcr.io/pxyup/fitter-mcp:playwright image, which bundles Chromium, Firefox and WebKit preinstalled (no "install": true needed).
Tools
ToolDescription
fitter_runRun a Fitter config passed inline (JSON or YAML string) and return the extracted data as JSON. Accepts an optional input value available in the config via {{{FromInput=.}}} / {{{FromInput=json.path}}}
fitter_run_fileSame as fitter_run but reads the config from a local .json/.yaml file
fitter_run_urlSame as fitter_run but downloads the config from an HTTP(S) URL, e.g. a raw GitHub link
fitter_inspect_urlFetch a URL and return a compact structure outline + candidate selectors/paths (gjson paths for JSON; repeated-element/list-row selectors for HTML) so the model authors a config first-try instead of guessing selectors and getting nulls. Detects client-rendered SPAs and can render them in a headless browser. Read-only — does not extract
fitter_validate_configValidate a config without executing it (structure, response_type, connector data source, model). Useful while iterating on a config
fitter_config_referenceReturn a condensed reference of the whole config format (connectors, parsers, model/field schema, placeholders, notifiers, references, limits) with working examples, so the model can author configs without external docs

The reference is also exposed as MCP resource fitter://config-reference for clients that support resources.

The config format is exactly the same as for Fitter_CLI: a top-level object with item (required), limits and references. Notifiers work too (the result is additionally pushed to http/telegram/redis/file/console); trigger_config and http_server are service-mode only and are ignored in MCP calls.

Remote / hosted mode (streamable HTTP)

By default fitter_mcp talks stdio. Pass --http to serve the streamable HTTP transport instead — for a shared team server, a container, or any remote deployment:

# serve MCP at http://<host>:8080/mcp (health probe at /healthz)

FITTER_MCP_AUTH_TOKEN=my-secret fitter_mcp --http :8080

register the remote endpoint in Claude Code

claude mcp add --transport http fitter http://localhost:8080/mcp --header "Authorization: Bearer my-secret"

  • --http (env FITTER_MCP_HTTP_ADDR) — listen address; stdio mode when empty
  • FITTER_MCP_AUTH_TOKEN — when set, every /mcp request must send Authorization: Bearer ; without it the endpoint is unauthenticated, so bind to localhost or put it behind a proxy
  • --stateless (env FITTER_MCP_STATELESS=true) — no per-session state, so replicas can sit behind a load balancer without sticky sessions
  • --metrics-addr (env FITTER_MCP_METRICS_ADDR) — serve Prometheus metrics on a separate address (e.g. 127.0.0.1:9091); works in stdio mode too; empty disables. Exposes MCP request counts by method, tool call durations by tool and outcome, and outbound HTTP request durations by host, method and status. The endpoint is unauthenticated — bind it to localhost or a private interface

The server shuts down gracefully on SIGINT/SIGTERM.

Docker

A slim multi-arch image (linux/amd64 + linux/arm64) ships with every release:

# hosted HTTP mode

docker run --rm -p 8080:8080 \ -e FITTER_MCP_HTTP_ADDR=:8080 \ -e FITTER_MCP_AUTH_TOKEN=my-secret \ ghcr.io/pxyup/fitter-mcp:latest

or stdio mode, spawned by the MCP client

claude mcp add fitter -s user -- docker run --rm -i ghcr.io/pxyup/fitter-mcp:latest

The slim image contains only the fitter binary and CA certificates: server/static/file connectors work, browser connectors (chromium/docker/playwright) do not.

For browser-based configs use the playwright variant, which bundles Playwright with Chromium, Firefox and WebKit (matched to the playwright-go version fitter is built against, so no "install": true is needed in configs):

docker run --rm -i ghcr.io/pxyup/fitter-mcp:playwright        # stdio mode

per-release tag: ghcr.io/pxyup/fitter-mcp:vX.Y.Z-playwright

It is built from Dockerfile.mcp-playwright; build with --build-arg PLAYWRIGHT_BROWSERS=chromium for a smaller Chromium-only image.

OAuth2 accounts in Docker

Both images ship fitter_cli, so the one-time OAuth2 login can run inside the container. Store the token on a volume mounted at /tokens (pre-created writable in the image) and share it with the MCP server:

# one-time login, device flow: no ports needed — open the printed url on any device

docker run --rm -it -v fitter-tokens:/tokens --entrypoint fitter_cli \ ghcr.io/pxyup/fitter-mcp:latest \ auth --provider github --client-id --client-secret --token-file /tokens/github.json

or browser flow (device flow not enabled for the app): publish the callback port and

bind on 0.0.0.0 so the published port reaches the listener; the browser still visits 127.0.0.1

docker run --rm -it -p 8988:8988 -e FITTER_AUTH_LISTEN=0.0.0.0 \ -v fitter-tokens:/tokens --entrypoint fitter_cli ghcr.io/pxyup/fitter-mcp:latest \ auth --provider github --client-id --client-secret --token-file /tokens/github.json

then run the MCP server with the same volume; configs reference "token_file": "/tokens/github.json"

stdio mode (spawned by the MCP client, no port):

docker run --rm -i -v fitter-tokens:/tokens ghcr.io/pxyup/fitter-mcp:latest

hosted HTTP mode (MCP endpoint on 8080, like the run examples above):

docker run --rm -p 8080:8080 -v fitter-tokens:/tokens \ -e FITTER_MCP_HTTP_ADDR=:8080 \ -e FITTER_MCP_AUTH_TOKEN=my-secret \ ghcr.io/pxyup/fitter-mcp:latest

Note: 8988 is only for the one-time browser-flow login; the MCP server itself needs no port in stdio mode and only 8080 in hosted HTTP mode.

Logged-in browser sessions in Docker

Browser sessions need the playwright image (the slim one has no browsers). The one-time headed login needs a display, so run it on the host, then bind-mount the session dir into the container (the image pre-creates a writable /sessions):

# on the host: log in once, save the session

fitter_cli browser-login --url https://example.com/login --storage-state ~/.fitter/sessions/example.json

run the MCP server with the sessions dir mounted; configs reference "storage_state_file": "/sessions/example.json"

docker run --rm -i -v ~/.fitter/sessions:/sessions ghcr.io/pxyup/fitter-mcp:playwright

Use a bind mount (not

只显示了开头部分;其余内容请在仓库中阅读

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