> For the complete documentation index, see [llms.txt](https://k-ai.gitbook.io/knowledge-ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://k-ai.gitbook.io/knowledge-ai/k-ai-mcp/connect-a-client.md). # Connect a client This page walks through installing the K-AI MCP servers (Retrieval and Audit) into the major MCP-compatible clients. Both servers use Streamable HTTP transport and the same OAuth 2.1 Authorization Server (`auth-api.kai-studio.ai`) — a token obtained from one is accepted on the other. | Client | Install method | Notes | | ----------------- | ------------------------------------------ | ------------------------------------------------------- | | Cursor | One-click deep-link (plus manual fallback) | Per-server deep-link. | | Claude Desktop | UI only (Custom Connectors) | Pro / Max / Team / Enterprise plan required. | | Mistral Le Chat | UI only (Custom MCP Connector) | May require Admin privileges. | | Other MCP clients | Manual OAuth + Streamable HTTP | See [OAuth flow](/knowledge-ai/k-ai-mcp/oauth-flow.md). | ## Cursor Cursor supports one-click installation via deep-links. Click each button to install (each opens Cursor and pre-fills the MCP config): [**Install K-AI Retrieval (stable)**](cursor://anysphere.cursor-deeplink/mcp/install?name=KAI%20Retrieval\&config=eyJ1cmwiOiJodHRwczovL2FwaS1yZXRyaWV2YWwua2FpLXN0dWRpby5haS9tY3AifQ==) [**Install K-AI Audit**](cursor://anysphere.cursor-deeplink/mcp/install?name=KAI%20Audit\&config=eyJ1cmwiOiJodHRwczovL2FwaS1hdWRpdC5rYWktc3R1ZGlvLmFpL21jcCJ9) Manual fallback — add to your Cursor MCP config at `~/.cursor/mcp.json` (global) or `.cursor/mcp.json` (per-project): ```json { "mcpServers": { "kai-retrieval": { "url": "https://api-retrieval.kai-studio.ai/mcp" }, "kai-audit": { "url": "https://api-audit.kai-studio.ai/mcp" } } } ``` {% hint style="info" %} On some Linux distributions (notably Debian), `cursor://` deep-links may fail to open the app. Use the manual config above if the buttons don't work. {% endhint %} On first use Cursor will open a browser tab for OAuth authentication. Sign in (local credentials or Microsoft SSO) and grant access; tokens are stored and refreshed automatically. ## Claude Desktop Claude Desktop does not expose a public deep-link scheme for MCP installation. Remote MCP servers must be added through the web Custom Connectors panel, not via `claude_desktop_config.json` (which is reserved for local stdio servers). {% tabs %} {% tab title="K-AI Retrieval" %} 1. Open [claude.ai](https://claude.ai) and sign in (requires Pro, Max, Team, or Enterprise plan). 2. Click your profile icon, then **Settings** → **Connectors**. 3. Click **+** then **Add custom connector**. 4. Enter the URL: `https://api-retrieval.kai-studio.ai/mcp`. 5. Complete the OAuth flow in the browser popup. {% endtab %} {% tab title="K-AI Audit" %} 1. Open [claude.ai](https://claude.ai) and sign in (requires Pro, Max, Team, or Enterprise plan). 2. Click your profile icon, then **Settings** → **Connectors**. 3. Click **+** then **Add custom connector**. 4. Enter the URL: `https://api-audit.kai-studio.ai/mcp`. 5. Complete the OAuth flow in the browser popup. {% endtab %} {% endtabs %} ## Mistral Le Chat Le Chat does not expose a public deep-link scheme. Add each connector through the web UI. {% tabs %} {% tab title="K-AI Retrieval" %} 1. Open [chat.mistral.ai](https://chat.mistral.ai) and sign in. 2. Click the **toggle panel** button (sidebar). 3. Expand **Intelligence** → click **Connectors**. 4. Click **+ Add Connector** → select the **Custom MCP Connector** tab. 5. Fill in the form: * **Connector name:** `kai-retrieval` * **Connection server:** `https://api-retrieval.kai-studio.ai/mcp` * **Description:** K-AI document retrieval * **Authentication:** OAuth 2.1 (auto-detected) 6. Click **Connect** and complete the OAuth flow. 7. In any chat, click the **Tools** button (four-squares icon) and enable the `kai-retrieval` connector. {% endtab %} {% tab title="K-AI Audit" %} 1. Open [chat.mistral.ai](https://chat.mistral.ai) and sign in. 2. Click the **toggle panel** button (sidebar). 3. Expand **Intelligence** → click **Connectors**. 4. Click **+ Add Connector** → select the **Custom MCP Connector** tab. 5. Fill in the form: * **Connector name:** `kai-audit` * **Connection server:** `https://api-audit.kai-studio.ai/mcp` * **Description:** K-AI document audit * **Authentication:** OAuth 2.1 (auto-detected) 6. Click **Connect** and complete the OAuth flow. 7. In any chat, click the **Tools** button (four-squares icon) and enable the `kai-audit` connector. {% endtab %} {% endtabs %} {% hint style="info" %} Adding Custom Connectors may require Admin privileges on the Le Chat workspace. {% endhint %} ## Custom MCP client For clients without UI integration, configure manually: * **K-AI MCP server URLs:** * Retrieval: `https://api-retrieval.kai-studio.ai/mcp` * Audit: `https://api-audit.kai-studio.ai/mcp` * **Transport:** Streamable HTTP, stateless. * **OAuth discovery:** GET `https://api-retrieval.kai-studio.ai/.well-known/oauth-authorization-server` or `https://api-audit.kai-studio.ai/.well-known/oauth-authorization-server`. Both return identical metadata pointing to `auth-api.kai-studio.ai`. * **Required flow:** Dynamic Client Registration (RFC 7591) + Authorization Code with PKCE (S256). Refresh tokens are rotated on every use. See [OAuth flow (detailed)](/knowledge-ai/k-ai-mcp/oauth-flow.md) for the full sequence, endpoint reference, and troubleshooting. The full OAuth 2.1 narrative is in [Authentication → OAuth 2.1](/knowledge-ai/authentication/oauth.md). ## First-connection flow (all clients) 1. The MCP client fetches the discovery document at `/.well-known/oauth-authorization-server`. 2. It registers itself dynamically (DCR — RFC 7591). 3. A browser window opens for user authentication (Microsoft SSO or local login). 4. Tokens are exchanged and stored by the client. 5. Subsequent tool calls are authenticated transparently; refresh tokens are rotated automatically every \~15 minutes. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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