프로토타입 · 미리 보기: 공식 레지스트리의 모든 서버를 담고 있으며 30분마다 동기화해요. 리뷰와 계정 기능은 다음 단계에서 열려요.
PopNx MCPAI를 쓰는 사람을 위한 MCP 서버 · 쉬운 말로 설명해요

ContextStream MCP Server

제작자: contextstream버전 0.4.81i★ –i내 컴퓨터에서 실행
레지스트리 이름io.github.contextstreamio/mcp-server

설치

개요

제작자가 쓴 설명(영어 원문)

ContextStream MCP server for code context, memory, search, and AI tools.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

  • 연결 방식: 내 컴퓨터에서 실행
  • 전송 방식: stdio
  • 카테고리: 검색 및 AI 기억
  • 입력해야 할 값: CONTEXTSTREAM_API_KEY

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

  • 기본 점검: 1개 중 0개 통과
  • 내 컴퓨터에서 내 사용자 계정의 권한(파일, 네트워크, 앱)으로 실행돼요.
  • 직접 입력할 값: CONTEXTSTREAM_API_KEY, CONTEXTSTREAM_API_URL

비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.

필요한 것

  • npmNode.js 설치(npx 명령어용)

어떤 앱을 쓰세요?

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요

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

터미널에서 이 명령어를 실행하세요

claude mcp add contextstreamio --env CONTEXTSTREAM_API_KEY=your-value --env CONTEXTSTREAM_API_URL=your-value -- npx -y @contextstream/mcp-server

실행하기 전에 빈 값을 채워 주세요.

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

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

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

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

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

  • CONTEXTSTREAM_API_KEY 비밀 필수 env
    ContextStream API key (create one at contextstream.io)
  • CONTEXTSTREAM_API_URL env
    API base URL

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

  • ! 주의

    제작자와 저장소 일치

    게시자(contextstreamio)가 저장소 소유자(contextstream)가 아니에요. 다른 사람이 등록했을 수 있어요

  • … 아직 점검 안 함

    계속 관리되고 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • … 아직 점검 안 함

    라이선스 있음

    아직 GitHub에서 이 저장소를 읽어 오지 않았어요

  • – 해당 없음

    엔드포인트 응답

    내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요

  • – 해당 없음

    OAuth로 로그인

    내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요

  • … 아직 점검 안 함

    도구 설명에 숨겨진 지시 없음

    내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요

검색 및 AI 기억 카테고리의 다른 서버와 비교i

  • 이 카테고리의 다른 서버 7234개 중 0%보다 스타가 많아요
  • 이 카테고리의 다른 서버 7234개 중 22%보다 최근에 레지스트리에 공개됐어요
  • 기본 점검 결과가 이 카테고리의 다른 서버 7234개 중 36%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

ContextStream MCP Server, 안전한가요?

해당하는 기본 점검 1개 중 0개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

입력해야 할 값: CONTEXTSTREAM_API_KEY

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.4.81)은 4개월 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Context7, Codebase Memory, Exa

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Context7

제작자: upstash

Up-to-date docs for AI agents

컴퓨터 또는 클라우드★ 64,224MIT3일 전 업데이트
설치

Codebase Memory

제작자: DeusData

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

내 컴퓨터에서 실행★ 48,148MIT20일 전 업데이트
설치

Exa

제작자: exa-labs

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

클라우드에서 실행★ 5,213MIT44일 전 업데이트
설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

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.

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 build --locked -p mcp-server --bin contextstream-mcp

cargo 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 g

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

PopNx에게 묻기