OpenSEO
Keyword research, site audits, rank tracking and AI visibility for your AI agent.
The context platform for AI agents: code search, team decisions, and grounded project context.
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
CustomizeConnectors
把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue
ContextStream MCP Serverhttps://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
+ConnectorsContextStream MCP Server
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
Plugins+Add custom MCP server
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
ContextStream MCP Serverhttps://mcp.contextstream.io/mcp开启新聊天,输入前先从插件列表中选择 ContextStream MCP Server
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
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add --transport http --scope user contextstream https://mcp.contextstream.io/mcp应能看到 ContextStream MCP Server 在列表中并显示已连接
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
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
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
通过网页连接的应用使用的地址
https://mcp.contextstream.io/mcpJSON 设置在下方“开发者专用”中
Claude Code
claude mcp add --transport http --scope user contextstream https://mcp.contextstream.io/mcpCursor (~/.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"
}
}
}Claude Code
claude mcp add --scope user contextstream --env CONTEXTSTREAM_API_KEY=your-value -- npx -y @contextstream/mcp-serverClaude 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"
}
}
}
}CONTEXTSTREAM_API_KEY 机密 必填 envCONTEXTSTREAM_API_URL env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。
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
服务器要求先登录,才会列出它的工具。
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
注册名称已通过 GitHub 账户 contextstream 验证,该账户拥有此仓库
代码最后更新于今天
使用 MIT
在 139 毫秒内响应(HTTP 401)
声明支持 OAuth 登录,你的 AI 应用可以带你去登录
尚未检查;我们会在检查端点时读取工具列表
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
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
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。
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。
你需要填写:CONTEXTSTREAM_API_KEY
两种方式都可以:安装在你的电脑上,或者连接云端版本。
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。
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)。
同一分类中有:OpenSEO, Exa, Mockserver, Microsoft Learn MCP, Docs
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
Keyword research, site audits, rank tracking and AI visibility for your AI agent.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Mock, record/replay, verify and chaos-test any HTTP, REST, gRPC or LLM dependency over MCP.
Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.
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.
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.
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?
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.
Each benchmark runs through the production API, is registered before its results are read, and is published with its method, confidence interval, and losses.
| Benchmark | ContextStream | Compared with |
|---|---|---|
| LongMemEval-S, all 500 questions | 96.8% (484/500); 96.0% on the half held out from tuning | Above 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 questions | 95.7% (1474/1540); 95.8% held out; 97.8% on the audited answer key | Above 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 queries | 98.77% best answer in the top 10; 100% a useful file in the top 10 | Embedding-only search 72.84% and ripgrep 42.59% on the same queries and judgments |
| Agent tasks, 8 tasks × 3 trials | 23/24 passed (96%); 9/9 on tasks that need team knowledge | 14/24 (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.
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.
form, with sizes (up to 6, such as instagram-post or linkedin-post) or a voice, and the plan keeps to it.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.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.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.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_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./studio serves only this tool, for Claude.ai or ChatGPT connectors, with OAuth tokens bound to that resource (read:studio, write:studio).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
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.
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.
contextstream-mcp setup --dry-run
contextstream-mcp doctor contextstream-mcp doctor --repair
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=.
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 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" }] } }
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