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。
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web-retrieval-mcp

作者:VelvetSP版本 0.1.2i★ –i在你的电脑上运行
注册名称io.github.VelvetSP/web-retrieval-mcp

安装

概览

作者提供的说明(英文原文)

MCP web search + tiered web fetch for AI agents (Exa, Firecrawl), SSRF-guarded, cross-platform.

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: 搜索与 AI 记忆
  • 你需要填写:EXA_API_KEY, FIRECRAWL_API_KEY

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)。
  • 需要你自己填写: EXA_API_KEY, FIRECRAWL_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 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": {
    "web-retrieval": {
      "command": "uvx",
      "args": [
        "web-retrieval-mcp"
      ],
      "env": {
        "EXA_API_KEY": "your-value",
        "FIRECRAWL_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add web-retrieval --env EXA_API_KEY=your-value --env FIRECRAWL_API_KEY=your-value -- uvx web-retrieval-mcp

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": {
    "web-retrieval": {
      "command": "uvx",
      "args": [
        "web-retrieval-mcp"
      ],
      "env": {
        "EXA_API_KEY": "your-value",
        "FIRECRAWL_API_KEY": "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": {
    "web-retrieval": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "web-retrieval-mcp"
      ],
      "env": {
        "EXA_API_KEY": "your-value",
        "FIRECRAWL_API_KEY": "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

  • EXA_API_KEY 机密 必填 env
    Exa API key (free tier at https://exa.ai)
  • FIRECRAWL_API_KEY 机密 必填 env
    Firecrawl API key (free tier at https://firecrawl.dev)

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 VelvetSP 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“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5692 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5692 个服务器的 16% 更新
  • 基础检查结果等于或优于此分类中其他 5692 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

web-retrieval-mcp 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?

你需要填写:EXA_API_KEY, FIRECRAWL_API_KEY

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(0.1.2)于5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 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

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

Context7

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 97.3万/周★ 6.4万前天更新

电脑或云端

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

作者:DeusData广泛使用↓ 1.8万/周★ 4.8万22天前更新

在你的电脑上运行

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

作者:exa-labs正在增长★ 52132个月前更新

在云端运行✓ exa.ai

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。

web-retrieval-mcp — reliable MCP web search and web fetch for AI agents

An open-source [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server for source-grounded web research. Connect Codex CLI and the Codex IDE extension, Claude Code, Claude Desktop, Cursor, ChatGPT desktop, or any other compatible MCP client to six read-only tools for Exa or Tavily search, resilient Exa → Camoufox → Tavily → Firecrawl page retrieval, AI/ML paper discovery, and developer-source search—with explicit provenance, optional local caching, and SSRF guards.

[Why use it?](#why-use-web-retrieval-mcp) · [Quick start](#quick-start) · [Tools](#six-read-only-tools) · [Routing](#how-retrieval-works) · [Configuration](#configuration-reference) · [Security](#security-model) · [FAQ](#frequently-asked-questions)

Why use web-retrieval-mcp?

Web research is more reliable when an agent can see where every result came from, choose the right retrieval strategy, and recover when one provider or page-access method fails. web-retrieval-mcp makes those controls part of the tool contract:

  • Keep sources separate. Default search returns one block per result with its own title, URL, highlights, and text, followed by a Sources trailer. Exa deep modes additionally return a clearly labeled synthesized answer, with grounding when Exa provides it, before the source-separated result blocks.
  • Use more than one retrieval path. Search can use Exa or Tavily and fall back to Firecrawl. Full-page fetches can escalate from indexed content to a local Camoufox browser, optional Tavily Extract, and Firecrawl.
  • Know what actually served the answer. Fetch responses identify the serving tier, cache state, semantic mode, and truncation instead of hiding the route.
  • Ask for the right shape. Fetch a readable page body, a concise summary, or a grounded answer to a question. Control freshness, rendering, domains, dates, result count, and per-result text size.
  • Search specialist corpora. Discover AI/ML papers, inspect query-relevant full-text passages, expand to related papers, and search developer documentation, READMEs, issues, and merged pull requests.
  • Own the deployment boundary. Run locally over stdio or host a loopback HTTP service; select providers and secret storage yourself; optionally cache completed fetches in a private Valkey sidecar.
  • Fail explicitly. Unsupported provider choices, missing optional packages, and unavailable credentials fail in the tool result. Tavily mappings, Firecrawl fallback filter gaps, and Exa category migrations are caller-visible; other Exa filter drops are written to server diagnostics.
How it compares with built-in agent web tools

Built-in capabilities vary by agent and can improve over time. The useful comparison is therefore not “all defaults are bad”; it is whether you need a portable, inspectable retrieval layer with controls your current client does not expose.

NeedTypical bundled search/fetch surfaceweb-retrieval-mcp
Search outputClient-defined result or synthesis formatDefault search returns source-separated blocks plus Sources; Exa deep modes add a labeled synthesis
Backend choiceProvider and routing are usually managed by the clientExa or Tavily search, with a disclosed Firecrawl fallback
Difficult pagesOne client-specific access pathIndexed content, guarded local browser rendering, Tavily Extract, and Firecrawl tiers
Retrieval intentUsually search or page textFull body, concise summary, or query-grounded page answer
Research discoveryGeneral web indexDedicated paper and developer-source tools in addition to web search
Freshness and filtersWhatever the client exposesDate windows, hour-level recency, domains, categories, result limits, and forced freshness
AuditabilityClient-specificFetch tier/cache/truncation disclosures; Tavily and Firecrawl search-fallback labels; explicit filter notices where supported
OperationsClient-defined; often hosted or opaqueLocal stdio or self-hosted loopback HTTP, optional private UDS cache
Security policyClient-specificInitial URL validation plus guarded browser requests and redirects

Use it as an independent complementary retrieval lane by default. If you want it to replace Claude Code's built-in WebSearch and WebFetch, the package also includes an optional, previewable hook installer.

Quick start

Python 3.10 or newer is required.

1. Install

For the complete feature set in an isolated environment:

pipx install --include-deps 'web-retrieval-mcp[all]'

camoufox fetch

--include-deps exposes Camoufox's own command from the isolated pipx environment; the second command downloads its managed browser. If you do not want local rendering, install the base package or selected non-render extras and skip the browser download.

For a lean Exa + Firecrawl installation:

pipx install web-retrieval-mcp

With uv installed, you can run the base package in a temporary isolated environment without a permanent install:

uvx web-retrieval-mcp

Or install into an existing virtual environment:

python -m pip install 'web-retrieval-mcp[all]'

python -m camoufox fetch

The browser download is required whenever you install the render extra and want Camoufox to serve render="auto" or render="always" calls.

Optional extras are composable:

ExtraAdds
tavilyTavily Search and Tavily Extract
renderLocal Camoufox/Playwright rendering
cacheValkey client for completed-result caching
keyringCross-platform native secret-store access
allEvery optional runtime capability above
2. Add provider credentials

For the broadest routing coverage, configure Exa and Firecrawl; add Tavily when you want provider-selectable search or another full-body fetch tier.

export EXA_API_KEY='<your-exa-api-key>'

export FIRECRAWL_API_KEY=' ' export TAVILY_API_KEY=' ' # optional

You do not need all three keys to start the server. Tools resolve credentials lazily and report what a selected route is missing. See Credential storage for a key file and OS secret-store alternatives.

All three providers advertised no-card entry allocations when checked on 2026-09-01; plans and unit costs can change, so check their live pricing before estimating a workload:

ProviderEntry allocation checked 2026-09-01Used for
Exa$20 signup credit plus $10 monthly API creditsDefault web search and first indexed-content fetch tier
Firecrawl1,000 credits per monthSearch/fetch fallback and research/developer indexes
Tavily1,000 API credits per monthOptional search provider and full-body extract tier
CamoufoxLocal open-source browserJavaScript-rendered page retrieval on your machine
3. Connect an MCP client

Codex CLI and the Codex IDE extension share MCP configuration. Add the server with the CLI, then verify it is registered:

codex mcp add web-retrieval -- web-retrieval-mcp

codex mcp list

With uvx and no prior install:

codex mcp add web-retrieval -- uvx web-retrieval-mcp

See OpenAI's Codex MCP documentation for the current CLI, IDE, and configuration-file details.

Claude Code:

claude mcp add web-retrieval -- web-retrieval-mcp

With uvx and no prior install:

claude mcp add web-retrieval -- uvx web-retrieval-mcp

Claude Desktop, Cursor, and other clients that accept an mcpServers object can use:

{

"mcpServers": { "web-retrieval": { "command": "web-retrieval-mcp" } } }

That configuration assumes the executable is on the client's PATH. For an uvx launch, use "command": "uvx" and "args": ["web-retrieval-mcp"]. If a desktop client does not inherit your shell environment, use the private key file described below or place literal key values in the client's protected environment configuration. Do not rely on ${VARIABLE} interpolation unless your client documents that behavior.

ChatGPT desktop and clients with different setup surfaces can connect through the MCP transport their current version supports. This server uses stdio by default and can also expose Streamable HTTP; consult the client's documentation for its configuration format and supported transports.

4. Give the agent a real task

Once the MCP server is connected, prompts can stay natural:

Search the web for the latest primary documentation about Python package metadata.

Keep each source separate and preserve its URL.

Fetch https://example.com/report, force a fresh retrieval, and answer only: What methodology did the authors use?

Find AI/ML papers about retrieval reranking, inspect the strongest paper for its reported benchmark result, then find newer work that cites it.

Search merged pull requests and documentation for the origin of this exact error: "transport closed".

Six read-only tools

All tools carry MCP's read-only annotation. MCP clients receive the complete generated input schema and descriptions when they connect.

ToolCompact signatureBest for
web_searchweb_search(query, num_results=8, mode="auto", …, provider=None)General web search through Exa or Tavily, with source-separated results and Firecrawl fallback
web_fetchweb_fetch(url, render="auto", max_chars=None, max_age_hours=None, mode="full", question=None, tavily=None)Readable page bodies, concise summaries, or grounded answers through a tiered fetch cascade
research_papersresearch_papers(query, k=8)Ranked AI/ML paper discovery through Firecrawl's Research Index
research_paperresearch_paper(paper_id, query=None)Paper metadata and optional query-relevant full-text passages for claim verification
research_similarresearch_similar(paper_id, intent, k=8, mode="similar", …)Related papers, citers, or references guided by a natural-language intent
research_githubresearch_github(query, k=8, passages=2, types=None, repos=None)Developer documentation, repository READMEs, issues, and merged pull requests

web_search supports relevance or date-oriented filters, domain inclusion/exclusion, publication windows, generated per-result summaries, and Exa's fast/deep search modes. Tavily receives equivalent controls where its API supports them; approximations and dropped controls are disclosed in the output.

The research-paper index is arXiv-oriented and best suited to AI/ML. For scholarly work outside that scope, use web_search(category="publication").

How retrieval works

Search routing

Exa is the default search provider. Select Tavily for one call with provider="tavily", or globally:

export WEB_SEARCH_PROVIDER=tavily

Only exa and tavily are accepted. If the

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