Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
The knowledge base your AI reads and writes, under your rules — over MCP, EU-hosted.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://app.brainattic.ai/api/mcpターミナルでこれを実行します
claude mcp add --transport http knowledge-base https://app.brainattic.ai/api/mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"knowledge-base": {
"url": "https://app.brainattic.ai/api/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"knowledge-base": {
"type": "http",
"url": "https://app.brainattic.ai/api/mcp"
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://app.brainattic.ai/api/mcpメニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名はドメイン brainattic.ai で確認済みです(レジストリがドメインの所有を確認しています)
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
作者のクラウドで動きます。インストール不要でインターネット経由でつながりますが、送った内容は作者のサーバーを通ります。
GitHubリポジトリの最終更新は–、最新バージョン(4.4.1)がレジストリに届いたのは7 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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
冒頭だけを表示しています。続きはリポジトリで読めます