Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
The knowledge base your AI reads and writes, under your rules — over MCP, EU-hosted.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
https://app.brainattic.ai/api/mcpRun this in your terminal
claude mcp add --transport http knowledge-base https://app.brainattic.ai/api/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"knowledge-base": {
"url": "https://app.brainattic.ai/api/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"knowledge-base": {
"type": "http",
"url": "https://app.brainattic.ai/api/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://app.brainattic.ai/api/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified against the domain brainattic.ai (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (4.4.1) reached the registry 7 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
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.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
Only the beginning is shown; read the rest in the repo