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PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

ContextStream MCP Server

作者:contextstream版本 1.0.79i★ 46i电脑或云端
注册名称io.github.contextstream/mcp-server

安装方法

What it does

The context platform for AI agents: code search, team decisions, and grounded project context.

  • Connects 电脑或云端
  • Account or key Cloud: Sign in to the service when you connect (OAuth) · Local: Needs CONTEXTSTREAM_API_KEY
  • Category 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

通过 5/5 项检查 · 你的提问会经过开发者的服务器(mcp.contextstream.io) · ✓ 命令已检查 2026年11月14日

第一步:你用哪个 AI?

选择你用的应用,步骤会显示在下方。

可连接 Claude · 约 2 分钟

不需要密钥,不用安装程序 · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个 · Team/Enterprise 方案由所有者(Owner)添加

  1. 打开 Claude 的 Connectors 页面

    CustomizeConnectors

    CustomizeConnectors1Add2https://…3Add4
  2. 点击“Add” → “Custom” → “Web”,填写这 2 项

    把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue

    Name · 名称ContextStream MCP Server
    Remote MCP server URL · 地址https://mcp.contextstream.io/mcp

    在 Claude 检测到的登录设置页点击 Continue · Authentication 按作者说明选择(Sign in now、Sign in when needed 或 No sign in),然后点击 Add

  3. 在聊天中开启

    +ConnectorsContextStream MCP Server

  4. 试一试

    用 ContextStream MCP Server 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude 说正在使用 ContextStream MCP Server,或回答中出现 ContextStream MCP Server 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

能否连接 ChatGPT 取决于方案

完整 MCP:网页版 ChatGPT Business、Enterprise 或 Edu · Pro:以读取/获取权限连接,修改数据的工具可能用不了 · Plus:官方文档尚未确认,如果在插件页看到添加自定义 MCP 的选项可以试试 · 仅限网页

  1. 在网页版 ChatGPT 打开添加 MCP 的页面

    Plugins+Add custom MCP server

    ChatGPTPlugins1+2https://…3Create4
  2. 填写名称和地址

    输入名称,在 Connection 下粘贴地址,勾选风险提示,然后点击 Create as a plugin

    Name · 名称ContextStream MCP Server
    Connection · 地址https://mcp.contextstream.io/mcp
  3. 在聊天中选择 ContextStream MCP Server

    开启新聊天,输入前先从插件列表中选择 ContextStream MCP Server

  4. 试一试

    用 ContextStream MCP Server 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 ChatGPT 说正在使用 ContextStream MCP Server,或回答中出现 ContextStream MCP Server 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 OpenAI 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Claude Code · 约 2 分钟

不需要密钥,不用安装程序

  1. 打开终端

    Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell

  2. 粘贴这条命令并按 Enter

    claude mcp add --transport http --scope user contextstream https://mcp.contextstream.io/mcp
  3. 在 Claude Code 中输入 /mcp

    应能看到 ContextStream MCP Server 在列表中并显示已连接

  4. 试一试

    用 ContextStream MCP Server 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Claude Code 说正在使用 ContextStream MCP Server,或回答中出现 ContextStream MCP Server 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同

可连接 Cursor · 约 2 分钟

不需要密钥,不用安装程序

  1. 点击这个按钮打开 Cursor

    在 Cursor 中打开

    Cursor 会请你确认安装,点击 Install

  2. 在 Cursor 中以 Agent 模式打开 AI 聊天

  3. 试一试

    用 ContextStream MCP Server 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 Cursor 说正在使用 ContextStream MCP Server,或回答中出现 ContextStream MCP Server 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同

可连接 VS Code · 约 2 分钟

不需要密钥,不用安装程序

  1. 点击这个按钮打开 VS Code

    在 VS Code 中打开

    VS Code 会请你确认安装,点击 Install

  2. 在 VS Code 中以 Agent 模式打开 AI 聊天

  3. 试一试

    用 ContextStream MCP Server 告诉我你能帮我做什么,然后做一件给我看

    ✓ 如果 VS Code 说正在使用 ContextStream MCP Server,或回答中出现 ContextStream MCP Server 的工具名称,就表示连接成功

菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同

其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看

查看所有支持 MCP 的应用 →

通过网页连接的应用使用的地址

地址https://mcp.contextstream.io/mcp

JSON 设置在下方“开发者专用”中

卡住了?问问正在用 ContextStream MCP Server 的人💬 讨论 →
开发者专用:终端命令和 JSON 设置

通过网页连接

Claude Code

claude mcp add --transport http --scope user contextstream https://mcp.contextstream.io/mcp

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "contextstream": {
      "url": "https://mcp.contextstream.io/mcp"
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "contextstream": {
      "type": "http",
      "url": "https://mcp.contextstream.io/mcp"
    }
  }
}

安装在电脑上

Claude Code

claude mcp add --scope user contextstream --env CONTEXTSTREAM_API_KEY=your-value -- npx -y @contextstream/mcp-server

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "contextstream": {
      "command": "npx",
      "args": [
        "-y",
        "@contextstream/mcp-server"
      ],
      "env": {
        "CONTEXTSTREAM_API_KEY": "your-value"
      }
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "contextstream": {
      "command": "npx",
      "args": [
        "-y",
        "@contextstream/mcp-server"
      ],
      "env": {
        "CONTEXTSTREAM_API_KEY": "your-value"
      }
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "contextstream": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@contextstream/mcp-server"
      ],
      "env": {
        "CONTEXTSTREAM_API_KEY": "your-value"
      }
    }
  }
}

需要你填写的值

  • CONTEXTSTREAM_API_KEY 机密 必填 env
    ContextStream API 密钥
    查看英文原文ContextStream API key
  • CONTEXTSTREAM_API_URL env
    ContextStream API 的基础 URL
    查看英文原文ContextStream API base URL

说明为自动翻译,变量名保持原样;不确定时请查看原文。

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。

一览

每周下载量i
3,724/周
连接方式
电脑或云端
传输方式
stdio, streamable-http
最新版本i
1.0.79
发布到注册中心i
2026年11月14日
代码最后更新i
2026年11月15日
作者
contextstream
软件包
npm: @contextstream/mcp-server
注册状态
活跃

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。

通过互联网连接,适用于

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

在你的电脑上运行,适用于

ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast

全部应用及其优缺点 →

它能做什么

服务器要求先登录,才会列出它的工具。

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15日

  • ✓ 通过

    作者与仓库一致

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

  • ✓ 通过

    仍在维护

    代码最后更新于今天

  • ✓ 通过

    有许可证

    使用 MIT

  • ✓ 通过

    端点有响应

    在 139 毫秒内响应(HTTP 401)

  • ✓ 通过

    使用 OAuth 登录

    声明支持 OAuth 登录,你的 AI 应用可以带你去登录

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

已公开的漏洞(OSV.dev)

OSV.dev 中没有 @contextstream/mcp-server@1.0.79 的记录

只检查这个版本的包本身,不包括所有依赖 · 检查于 2026年11月15日

我们检查什么 → · JSON

作者:申请重新检查或报告信息错误

讨论

提问、分享技巧或报告无法使用。按“有帮助”数量排序。

还没有帖子,欢迎第一个提问或分享。

此处内容由用户撰写,不代表 PopNx 团队。

登录后发帖

用户评价

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登录后写评价

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 6156 个服务器的 96%
  • 发布到注册中心的时间比此分类中其他 6156 个服务器的 97% 更新
  • 基础检查结果等于或优于此分类中其他 6156 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

ContextStream MCP Server 安全吗?

它在 5 项适用的基础检查中通过了 5 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:CONTEXTSTREAM_API_KEY

它在我的电脑上运行还是在云端?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于今天,最新版本(1.0.79)于昨天进入注册中心。

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。它通过 URL 连接,因此也能用于接受远程 MCP 的应用,例如网页版 ChatGPT(Business 及以上为完整 MCP;Pro 为只读)。

有什么可以替代它?

同一分类中有:OpenSEO, Exa, Mockserver, Microsoft Learn MCP, Docs

功能相近的其他选择

同一分类、其他作者、命令已通过检查。官方的排在前面,再按星标排序。

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

OpenSEO

Keyword research, site audits, rank tracking and AI visibility for your AI agent.

作者:every-app广泛使用★ 2.8万昨天更新

在云端运行✓ everyapp.com

Exa

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

作者:exa-labs广泛使用★ 52322个月前更新

在云端运行✓ 服务方 · exa.aiPopNx 团队已实际试用

Mockserver

Mock, record/replay, verify and chaos-test any HTTP, REST, gRPC or LLM dependency over MCP.

作者:mock-server正在增长★ 501019天前更新

在你的电脑上运行✓ 服务方 · mock-server.com

Microsoft Learn MCP

Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.

作者:MicrosoftDocs广泛使用★ 199012个月前更新

在云端运行✓ 服务方 · microsoft.comPopNx 团队已实际试用

Docs

Search and read Empryo's documentation. Read-only, no auth, no local access.

作者:proxysoul正在增长★ 16062个月前更新

在云端运行✓ empryo.com
  • OpenSEO — 在云端运行,无需安装 · 不需要密钥
  • Exa — 在云端运行,无需安装 · 不需要密钥 · 在 Claude 的目录中
  • Mockserver — 需要安装在电脑上 · 不需要密钥
  • Microsoft Learn MCP — 在云端运行,无需安装 · 不需要密钥 · 在 Claude 的目录中
  • Docs — 在云端运行,无需安装 · 不需要密钥

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。

ContextStream MCP Server

The context platform for AI agents.

Your agent knows code. Give it the decisions behind yours.

Connect your code, docs, and conversations so your agents can find the right files, recall saved decisions, and build on past work across sessions and tools.

The numbers, their sources, and what they do not claim are under Benchmarks.

Start free with MCP

10,000 monthly credits. No credit card required.

Works with Claude Code, Cursor, Codex, GitHub Copilot, Gemini CLI, Qwen Code, Kimi Code, Muse Code, ZCode, Zed, and more MCP clients, on Claude, GPT, Gemini, Kimi, GLM, Qwen, and other models. Create your account or sign in during MCP onboarding. No separate website signup needed.

macOS and Linux

curl -fsSL https://contextstream.io/scripts/mcp.sh | bash

Windows PowerShell

irm https://contextstream.io/scripts/mcp.ps1 | iex

Paste the command into your terminal and follow onboarding to connect your project and supported editor. Restart your editor after setup.

What gets installed and indexed? · Supported clients · Setup guide · Prefer to start on the web?

Make the next session useful

Ask your connected agent:

Use ContextStream to find the files relevant to my next change. Cite the

sources and retrieve any saved project decisions that should guide the work.

Then ask it to save a real decision and its reason. Start a new session and retrieve that decision without explaining it again. Indexing supplies code context; it cannot recover every undocumented decision.

Benchmarks

Each benchmark runs through the production API, is registered before its results are read, and is published with its method, confidence interval, and losses.

BenchmarkContextStreamCompared with
LongMemEval-S, all 500 questions96.8% (484/500); 96.0% on the half held out from tuningAbove Mastra (94.87%) and supermemory (85.4%) on the same official GPT-4o judge. Level with agentmemory's self-reported 96.2%, which is inside our 95% interval
LoCoMo, all 1,540 questions95.7% (1474/1540); 95.8% held out; 97.8% on the audited answer keyAbove every system in the EverMemOS paper's same-judge table: EverMemOS 93.05%, Zep 85.22%, MemOS 80.76%, MemU 66.67%, Mem0 64.20%
Code search, 177 judged developer queries98.77% best answer in the top 10; 100% a useful file in the top 10Embedding-only search 72.84% and ripgrep 42.59% on the same queries and judgments
Agent tasks, 8 tasks × 3 trials23/24 passed (96%); 9/9 on tasks that need team knowledge14/24 (58%) and 0/9 with the repository alone

61 ms median server-side search time (127 ms p95) in the October 27 production run. End to end it was 223 ms, because the client ran in a different region from the one serving the workspace. Your latency depends on your distance from that region.

Competitor figures are as each vendor or the EverMemOS paper published them; we did not re-run them, and readers and judges differ across rows. The code-search baselines come from the August 1 run on the same queries. The agent-task result uses one repository and one agent model, so treat it as directional. Results, methodology, and limitations.

ContextStudio

For people ContextStream Create offers one-prompt making to, the server adds one tool, studio: ask for a film, a product explainer filmed from your connected product, an image, sound or music in plain words, and ContextStudio's producer plans the pieces from what your team knows (brand kit, docs, decisions, connected products). There are no models to pick.

  • Brand work by name. Brand images (social sets in each network's size, ad sets, hero and product shots, posters and flyers with print PDFs, email headers, brand graphics) and brand sounds (sonic logos, music beds, loops, effect packs, voice-overs, podcast intros and outros): pass form, with sizes (up to 6, such as instagram-post or linkedin-post) or a voice, and the plan keeps to it.
  • Plan, then price. plan returns the pieces and one price ("up to N credits, likely about M") and spends nothing. Pass what your agent knows that the workspace may not (the diff it just made, release notes, the doc it has open) as context; the producer reads it next to the team's own context.
  • Your go-ahead. make spends at most the plan's price, and only after you agree: a client that can ask you (MCP elicitation, or a stateless input_required result) asks you itself; otherwise the agent passes the price you accepted.
  • Following it. status reports each piece while it waits (with notifications/progress where the call asks for them); a product film takes 13 to 21 minutes. result shows images inline and links video and sound (signed links valid about 15 minutes), with each piece's placard. Brand work comes as files, each with its own link: every size as PNG, JPG and WebP with a ZIP of the set, a print PDF, or WAV and MP3 for the web with a broadcast master and stems, plus alt text, a caption and the checks it was held to.
  • Revising. revise starts from a made image or sound: a variation (more like it), a revision (it, changed as you say) or a resize (an image in new sizes). Also stop, library, brand and products.
  • Email, where Create offers it. Campaigns sent through your team's own Resend account. email_draft writes one in your brand from a prompt ("announce our winter sale to customers") and sends nothing; email_audiences, email_campaigns, email_test (to your own address or Resend's test addresses), email_cancel and email_report (a campaign's delivery, opens, clicks, bounces and complaints, or the workspace's trends). email_send goes only with your go: the client asks you when it can; otherwise the agent shows you the campaign and its recipient count and passes the count you agreed to. email_preview gives a link to share that shows the email in Gmail, Outlook and Apple Mail mockups (desktop, tablet and phone, light and dark, images on or off), with the inbox line and what to check. email_revise changes a draft from plain words ("shorter subject") or sets its subject and preview line; email_duplicate makes a draft copy. email_contacts lists, adds (with where they agreed to hear from you) or unsubscribes contacts; erasing one can't be undone, so it is the delete tool's (studio.email_contact_erase), after your go; email_unsubscribes shows the suppression list with why and when, and takes an address off it only with your go. Resend is connected in the studio, never through an agent: the tool refuses anything shaped like a Resend key.
  • Connector. The hosted path /studio serves only this tool, for Claude.ai or ChatGPT connectors, with OAuth tokens bound to that resource (read:studio, write:studio).

Data controls

Scoped access. Traceable sources. Configurable capture. Indexing sends eligible source contents to ContextStream for hosted search. Transcript saving and local Git metadata capture are on by default and can be turned off. Review data handling and controls before connecting sensitive projects.

Live run progress from the hooks (a run that starts when your agent takes up a ticket, stays live while the session works and ends with it, without the agent having to report) is off by default. Turn it on for yourself with CONTEXTSTREAM_RUN_PROGRESS_AUTO=on in the environment your editor starts with; what it sends.

Other installation options and troubleshooting

npm (Node.js 20+)
npx -y @contextstream/mcp-server@latest setup

The npm launcher downloads the native Rust binary for your platform and verifies its SHA-256 checksum. Pin an exact package version for production automation.

Hosted MCP without a local process

For clients supporting Streamable HTTP and OAuth, the hosted endpoint is:

https://mcp.contextstream.io/mcp?default_context_mode=fast

Supported clients lists one-line add commands for Claude Code, Codex, Gemini CLI, Qwen Code, Copilot CLI, and Droid, and one-click install for VS Code. Use the MCP documentation for other clients and stdio alternatives. A hosted connection alone does not sync your local checkout.

Preview or diagnose setup
contextstream-mcp setup --dry-run

contextstream-mcp doctor contextstream-mcp doctor --repair

Scripted and CI setup

For automation, wrap the install in pipefail so it fails when the download fails, instead of reporting success after installing nothing:

bash -o pipefail -c 'curl -fsSL https://contextstream.io/scripts/mcp.sh | bash'

setup --yes reads the key from CONTEXTSTREAM_API_KEY or saved credentials, and needs --workspace-id when the account has more than one workspace:

export CONTEXTSTREAM_API_KEY=...   # or: printf %s "$KEY" | contextstream-mcp configure --api-key-stdin

contextstream-mcp setup --yes --editors=claude --workspace-id= --project-path=.

Package Bouncer (opt-in)

A hook for Claude Code and Cursor that checks the packages an install command names against their public registry before the command runs. It covers npm, pnpm, yarn, bun, npx, pip, uv, uvx, pipx, poetry and cargo, including claude mcp add ... -- npx ....

  • It denies a package the registry does not have, naming the popular package it looks like. An agent may have invented the name, and anyone can register it.
  • It asks before a barely downloaded lookalike of a popular package.
  • It allows everything else, including whenever a lookup fails or takes too long.

It skips projects and commands that use a private registry (.npmrc, pip.conf, uv or poetry sources, --registry, --index-url). CONTEXTSTREAM_PACKAGE_BOUNCER=off turns it off.

Claude Code: add this entry to PreToolUse in ~/.claude/settings.json, next to the hooks setup installed. update-hooks leaves it alone.

{ "matcher": "Bash", "hooks": [{ "type": "command", "command": "contextstream-mcp hook package-bouncer", "timeout": 8 }] }

Cursor (~/.cursor/hooks.json):

{ "version": 1, "hooks": { "beforeShellExecution": [{ "command": "contextstream-mcp hook package-bouncer" }] } }

Open source and contributing

This repository contains the MIT-licensed Rust MCP server, client, editor setup, and release tooling. The hosted backend is separate and is not included here. See the architecture, release integrity, and latest release.

cargo bu

只显示了开头部分;其余内容请在仓库中阅读