ContextStream MCP Server

io.github.contextstream由 GitHub 账号 contextstream 发布v1.0.72更新于 Nov 8, 2026

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

发布方自己的服务:Stream Estate

已验证Streamable HTTP可网页运行知识与记忆开发者工具媒体与设计

概览

AI 生成的概览

ContextStream 为 AI 代理提供有依据的项目上下文:代码搜索、已保存的团队决策、跨会话回忆,以及用于品牌素材和邮件活动的 studio 工具。

可以做什么
  • 搜索代码与文档,找出与本次改动相关的文件并引用来源
  • 保存和检索项目决策与过往工作,跨会话、跨工具复用
  • 通过 studio 工具规划、报价、生成、修改并跟踪品牌图片、声音和视频
  • 通过团队自己的 Resend 账户起草、预览、测试和发送邮件活动,并管理联系人与受众
  • 可选地在执行前核对安装命令中的包是否存在于公共注册表
适用场景
适合代理在代码库中长期工作、需要回忆先前决策的场景,也适合团队希望不离开助手就基于自身文档、决策和品牌素材生成品牌资产与邮件活动的场景。
运行要求
可使用带 OAuth 的托管 Streamable HTTP 端点,或通过 npm 包(Node.js 20+)或提供的安装脚本在本地安装;需在引导过程中创建 ContextStream 账户,脚本化安装需在 CONTEXTSTREAM_API_KEY 中提供 API 密钥;账户有多个工作区时还需工作区 ID。
安装前请注意
索引会把符合条件的源内容发送到 ContextStream 用于托管搜索,会话记录保存和本地 Git 元数据采集默认开启,连接敏感项目前请先查看数据控制设置。studio 的 make 与 email_send 会消耗额度或真实发送邮件,设计上需要你明确同意;删除联系人不可撤销。Resend 凭据在 studio 中连接,不通过代理传入。

安装

在 SourceWeft 中

  1. 打开 控制台中的 ContextStream MCP Server,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.contextstream%2Fmcp-server/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

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

README

[ContextStream]

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.

[ContextStream benchmarks: LongMemEval-S 96.8% (484 of 500), LoCoMo 95.7%, code search 98.77% best answer in the top 10, agent tasks 96% (23 of 24, up from 58% without it)]

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

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

Windows PowerShell

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.

Other installation options and troubleshooting

npm (Node.js 20+)

bash
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:

text
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

bash
contextstream-mcp setup --dry-runcontextstream-mcp doctorcontextstream-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
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:

bash
export CONTEXTSTREAM_API_KEY=...   # or: printf %s "$KEY" | contextstream-mcp configure --api-key-stdincontextstream-mcp setup --yes --editors=claude --workspace-id=<UUID> --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.

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

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

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.

bash
cargo build --locked -p mcp-server --bin contextstream-mcpcargo test --locked --workspace

Use the pinned Rust toolchain. For contribution checks and commit sign-off, read CONTRIBUTING.md. Report vulnerabilities using SECURITY.md. See LICENSE, NOTICE, and GOVERNANCE.md for licensing, trademarks, and project governance.


Let humans be human.

Docs · Pricing · Integrations · Benchmarks

Optional deep project learning

Deep project learning starts off for new accounts. Interactive setup offers it once per account (or once when terms change) and remembers if you decline; plain contextstream-mcp setup --yes preserves your current choice.

bash
contextstream-mcp configure --account-learning status   # show current consent statecontextstream-mcp configure --account-learning on       # open privacy page in browser (or print URL)contextstream-mcp configure --account-learning off      # withdraw consent and queue deletion

--deep-learning is accepted as an alias for --account-learning. Only a person can grant consent by ticking the unchecked box on the signed-in privacy page (https://contextstream.io/dashboard/account/privacy); agents and API keys cannot consent for you. Doctor and init show status only. See data handling and controls.

来源:README.md,提交 7da0637

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

39
  1. v1.0.71Nov 6, 2026
  2. v1.0.70Nov 6, 2026
  3. v1.0.69Nov 5, 2026
  4. v1.0.68Nov 5, 2026
  5. v1.0.66Nov 4, 2026
  6. v1.0.65Nov 4, 2026
  7. v1.0.64Nov 4, 2026
  8. v1.0.62Nov 4, 2026
  9. v1.0.60Nov 3, 2026
  10. v1.0.59Nov 3, 2026
  11. v1.0.55Nov 1, 2026
  12. v1.0.54Nov 1, 2026
  13. v1.0.53Nov 1, 2026
  14. v1.0.48Oct 31, 2026
  15. v1.0.46Oct 30, 2026
  16. v1.0.44Oct 30, 2026
  17. v1.0.43Oct 30, 2026
  18. v1.0.42Oct 29, 2026
  19. v1.0.31Oct 26, 2026
  20. v1.0.30Oct 26, 2026
  21. v1.0.29Oct 25, 2026
  22. v1.0.28Oct 22, 2026
  23. v1.0.27Oct 22, 2026
  24. v1.0.26Oct 19, 2026
  25. v1.0.25Oct 16, 2026
  26. v1.0.24Oct 13, 2026
  27. v1.0.22Oct 13, 2026
  28. v1.0.20Oct 10, 2026
  29. v1.0.18Oct 7, 2026
  30. v1.0.17Oct 6, 2026
  31. v1.0.16Oct 6, 2026
  32. v1.0.15Oct 5, 2026
  33. v1.0.13Oct 5, 2026
  34. v1.0.12Oct 3, 2026
  35. v1.0.11Oct 1, 2026
  36. v1.0.10Sep 29, 2026
  37. v1.0.9Sep 27, 2026
  38. v1.0.8Sep 25, 2026
  39. v1.0.7Sep 16, 2026

评分

已满足适用检查项的 85%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

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    请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。

  • 描述必需15 分
  • 图标10 分
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其他 Stream 集成