> For the complete documentation index, see [llms.txt](https://docs.bito.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bito.ai/ai-architect/installation/install-ai-architect-self-hosted/standalone-deployment.md). # Standalone deployment Run AI Architect privately on your own workstation. Setup takes about 5 to 10 minutes. Your AI coding agent connects automatically during installation. {% hint style="info" %} Sharing with a team or installing on a server? Use the Enterprise deployment guide instead. {% endhint %} ## Before you begin Have the following ready. See [Prerequisites & requirements](/ai-architect/installation/install-ai-architect-self-hosted/prerequisites-and-requirements.md) for creation links and details. | Requirement | Notes | | ------------------------ | ------------------------------------------------------------------ | | Bito API key | [alpha.bito.ai/home/advanced](https://alpha.bito.ai/home/advanced) | | Git provider token (PAT) | GitHub, GitLab, Bitbucket, or Azure DevOps | | Your email (optional) | Associates the automatic coding-agent registration with you | | Docker Desktop 20.10+ | With Compose v2 | | Free ports | 5001-5006 on localhost | {% stepper %} {% step %} ### Pre-seed your configuration (optional) To install **without prompts**, provide your configuration before running the installer. Skip this step to install interactively, and the installer asks for each value instead. ```shellscript mkdir -p ~/.bitoarch ``` ```shellscript cat > ~/.bitoarch/install.yaml <<'EOF' bito_api_key: "" git: provider: github access_token: "" user_email: "you@company.com" # associates coding-agent registration with you EOF ``` Start from the full template, [install.default.yaml](https://raw.githubusercontent.com/gitbito/ai-architect/refs/heads/main/install.default.yaml), to pre-seed any option: LLM provider keys, Insights, custom ports, and more. {% endstep %} {% step %} ### Install and index ```shellscript curl -fsSL https://aiarchitect.bito.ai/standalone/install.sh | bash ``` If you pre-seeded your configuration, the installer runs without prompts. Otherwise, it asks for your Bito API key and Git provider token. The installer validates prerequisites, deploys the services, then **fetches your repository list** from your Git provider and asks how to proceed: * **Auto (recommended)**: saves the fetched repository list and starts indexing automatically (about 3-10 minutes per repository). * **Manual**: follow the steps shown in the terminal to complete configuration. In summary: 1. `bitoarch config edit repos` (review or trim the list, as each indexed repository consumes LLM tokens) 2. `bitoarch add-repos` (apply the list) 3. `bitoarch index-repos` (start indexing) On success, the installer prints your **MCP URL and access token**. **Your AI coding agent connects automatically.** Standalone serves MCP over HTTPS at `https://localhost:5001/mcp` with a locally trusted certificate, and the installer registers this endpoint in every detected AI coding agent (Claude Code, Cursor, Windsurf, VS Code, Junie, and JetBrains AI Assistant). During installation you are asked for an email to associate with this registration (or pre-seed `user_email`); press Enter to skip it. Restart each tool when prompted. No further setup is needed. ```shellscript bitoarch mcp-info # view the MCP URL, token, and authentication mode anytime ``` {% hint style="info" %} Installed a new IDE after setup? Register it with `bitoarch mcp-install`. Re-running the install command is also safe: existing configuration is reused with no prompts. {% endhint %}
Manual agent configuration (if an IDE is not auto-detected) ```json { "mcpServers": { "BitoAIArchitect": { "url": "https://localhost:5001/mcp", "headers": { "Authorization": "Bearer ", "x-email-id": "you@company.com" } } } } ``` Run `bitoarch mcp-info` for your URL and token. The `x-email-id` header is the email associated with your registration. For per-tool guidance, see: * [Quick MCP integration with AI coding agents](/ai-architect/quick-mcp-integration-with-ai-coding-agents.md) * [Integrating AI Architect with your tools](/ai-architect/integrating-ai-architect-with-your-tools.md)
{% endstep %} {% step %} ### Verify the installation ```shellscript bitoarch status # all services healthy bitoarch index-status # reaches "completed" bitoarch mcp-test # end-to-end MCP check passes ``` Setup is complete. Ask your AI coding agent a cross-repository question to confirm it is using AI Architect context. {% endstep %} {% endstepper %} ## Next steps * [Operations & troubleshooting](/ai-architect/installation/install-ai-architect-self-hosted/operations-and-troubleshooting.md) * [CLI command reference](/ai-architect/installation/install-ai-architect-self-hosted/cli-command-reference.md) Optional: connect the AI Code Review Agent for codebase-aware reviews, or enable Insights. {% hint style="info" %} The MCP certificate **renews automatically** every day through your OS scheduler. Check it anytime with `bitoarch mcp-cert status`. {% endhint %} --- # 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. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.bito.ai/ai-architect/installation/install-ai-architect-self-hosted/standalone-deployment.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.