Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
The knowledge base your AI reads and writes, under your rules — over MCP, EU-hosted.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:
https://app.brainattic.ai/api/mcp터미널에서 이 명령어를 실행하세요
claude mcp add --transport http knowledge-base https://app.brainattic.ai/api/mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"knowledge-base": {
"url": "https://app.brainattic.ai/api/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"knowledge-base": {
"type": "http",
"url": "https://app.brainattic.ai/api/mcp"
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:
https://app.brainattic.ai/api/mcp메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 brainattic.ai 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(4.4.1)은 7일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
The knowledge base your AI reads and writes — under your rules.
Valuable knowledge gets scattered across private AI conversations, individual assistants and disconnected systems. brainattic gives people and AI agents a shared, persistent, governed knowledge base: one authoritative set of versioned documents, even when teammates use different AI clients. Human-defined permissions control access, rules guide how agents work, and revision history makes changes traceable and recoverable.
brainattic is not another AI chatbot, a chat-history archive, or a replacement for SharePoint, Git or your existing business systems. It holds the knowledge your team needs across them: decisions, procedures, customer context and project history. AI clients connect over the Model Context Protocol (MCP) to search, read and update it.
This repository documents the hosted brainattic MCP server: what it does, how to connect a client, and how to use it. It contains no server code. The service is hosted and operated by Finite Software Systems Ltd.
| MCP endpoint | https://app.brainattic.ai/api/mcp |
| Transport | Streamable HTTP |
| Authentication | OAuth 2.1, discovered automatically (dynamic client registration, no API key or client secret) |
| Official MCP Registry name | ai.brainattic/knowledge-base |
| Discovery card | https://brainattic.ai/.well-known/mcp/server.json |
| Product and sign-up | https://brainattic.ai |
| Connect guide | https://brainattic.ai/docs/connect |
| Support | https://brainattic.ai/support · hello@brainattic.ai |
Personal AI memory helps one person in one client. Shared knowledge lets the whole team build on a decision, correct it once and carry it into the next task without copying private chats or asking everyone to switch assistants.
Sales can work in ChatGPT, analysts in Claude, developers in VS Code with GitHub Copilot, and operations in Hermes. Each uses the same versioned knowledge, within their own permissions, while keeping their preferred tools and workflow.
Three distinct mechanisms keep that collaboration governed:
We built brainattic at Finite Software Systems Ltd to close exactly that gap in our own work. See [One knowledge base, every agent](docs/team-workflow.md) for a change request followed from the customer call through analysis, implementation, testing and shipping, and for how a new team member gets up to speed in a single conversation.
When you connect, your agent works inside your brainattic workspace with your own permissions. Each person signs in with their own account, so an agent can only reach what that person can.
The tools fall into these groups:
Your client discovers the current tool list when it connects. Every tool carries MCP annotations (readOnlyHint, destructiveHint, openWorldHint), so clients can ask before running a tool that changes or deletes data.
Core customer data is stored and processed on infrastructure controlled by Finite Software Systems Ltd in Bulgaria, European Union. Finite Software Systems Ltd operates its own infrastructure, colocated in a Tier 3+ data centre in Sofia. The data-centre operator provides the physical facility and its access controls, with no logical access to customer data.
Customer workspaces have logical tenant isolation, role-based permissions and individual user authentication. Access is protected by TLS; MCP connections use OAuth-based authentication. Finite Software Systems Ltd uses segmented networks, firewalls, restricted administrative access, operational and security logging and monitoring, and regular backups on EU infrastructure under its control. Finite Software Systems Ltd strictly follows its documented ISO 9001 and ISO/IEC 27001 procedures.
brainattic does not independently forward customer documents to third-party AI models. Your chosen AI client can receive content you explicitly request through the connector, subject to your permissions and that client's own policies. EU hosting does not determine where your AI provider processes that content. Optional integrations, such as Slack reminders, can also involve transfers outside the EEA; the published policies describe these and other limited exceptions.
For the published security measures, data-handling details and contractual commitments, see Security, the Privacy Policy and the Data Processing Agreement.
Finite Software Systems Ltd is ready to offer on-premises brainattic deployment for organisations that need the knowledge base on their own infrastructure, with control over where it runs and how it is operated. Each deployment is planned customer by customer: we work with you to agree the requirements, scope, integrations and delivery timeline.
A pilot-first approach can validate feasibility and practical value before moving to your on-premises solution with Finite Software Systems Ltd. Talk to us about your needs and the right deployment path for your organisation.
AI clients and integrations must also meet your data-handling requirements; hosting the knowledge base on-premises alone does not control where those services process content.
Every client uses the same URL: https://app.brainattic.ai/api/mcp. On first use the client opens a browser window. Sign in to brainattic and approve access. You never paste a key or a secret.
Add the server to .vscode/mcp.json in your project, or to your user configuration with the MCP: Add Server command:
{
"servers": { "brainattic": { "type": "http", "url": "https://app.brainattic.ai/api/mcp" } } }
Start the server from the file or the MCP view, complete the sign-in, and the brainattic tools appear in Copilot's agent mode.
Open Settings → Connectors → Add custom connector. Name it brainattic, paste the URL and connect. Claude walks you through the sign-in.
claude mcp add --transport http brainattic https://app.brainattic.ai/api/mcp
Then run /mcp inside Claude Code and choose brainattic to sign in.
Open Settings → Connectors, add a custom connector with the URL above and complete the sign-in. Custom MCP connectors need a ChatGPT plan that supports them.
Add to ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (one project):
{
"mcpServers": { "brainattic": { "url": "https://app.brainattic.ai/api/mcp" } } }
A workspace administrator opens Connectors, clicks + Add Connector → Custom MCP Connector, names it brainattic and pastes the URL. In a chat, enable brainattic under Tools.
gemini extensions install https://github.com/rutash/brainattic-gemini-cli
Then run /mcp auth brainattic inside Gemini CLI.
Point the client at https://app.brainattic.ai/api/mcp (Streamable HTTP). OAuth 2.1 is discovered from the server, as the MCP authorization specification describes. An unauthenticated request returns 401 with a bearer challenge that tells the client where to sign in.
brainattic works best as a conversation. Your agent proposes, you adjust and approve, and the agent carries it out. Everything it writes is saved as a revision you can inspect or roll back. The steps below are a good first session.
Rules are short, human-written conventions that your agent reads before it writes. Examples are the language to write in, date formats, naming, status words, and what must never be written down (secrets, credentials, personal data). Each workspace comes with a workspace rules document from day one, so your first question should be:
"What rules apply before writing in this workspace? Read them and explain them to me in plain words."
If the rules are filled in, the agent summarises them and explains how it will follow them. If they are still empty, it tells you so, which is your cue for step 2.
Shape the rules in conversation instead of writing them from scratch:
"Suggest workspace rules for us: language, date format, document naming, status vocabulary and
a never-write-down list. Base them on how I work. Draft them for my review and don't save anything yet."
Push back, add, remove and refine until the draft fits. Then say *"Save these as the workspace rules."* Workspace rules need an admin role. Editors can set rules for a project or a group, and an admin can also edit any rules in the web app under Admin → Rules. From the next write on, every connected agent reads the approved rules, not just the one you talked to.
Ask the agent to explain the model using examples from your own work:
"Explain how workspaces, projects, groups, documents, rules and skills relate in brainattic.
Use examples from my own work."
The short version:
| Concept | What it is | Example |
|---|---|---|
| Workspace | The boundary around your team's knowledge and permissions. Each person has a role in it: Viewer, Editor or Admin. | "Acme Ltd" |
| Project | A document's optional *primary home*. A document belongs to at most one project, and a project can have a hand-written overview ("start here") document. | "Customer onboarding" |
| Group | A cross-cutting label. A document can carry several groups, or none, across projects. Groups are not sub-projects. | "customer-facing", "needs-review" |
| Document | A versioned Markdown page. Every saved change is a revision. | "Onboarding checklist" |
| Rules | Conventions at workspace, project or group scope. Agents read them in that order, and the more specific scope wins a direct conflict. | "Every procedure starts with a one-line purpose" |
| Skills | Reusable step-by-step procedures for agents, which rules can recommend. | "How to file meeting notes" |
Your agent already knows a lot about you: earlier conversations, the projects you've di
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