How to save Quake AI knowledge to Obsidian, Git, or Notion
How to save Quake AI knowledge to Obsidian, Git, or Notion
Every Quake AI MCP tool returns a portable Markdown artifact alongside its data. A connected assistant can file that artifact straight into your Obsidian vault, a Git repository, or Notion, so the documentation, templates, and launch handoffs you pull during a session stay in your own notes.
This page covers the save workflow for each destination, the export_okf tool for saving a whole linked knowledge bundle, and the fallback for tools without MCP support.
Prerequisites
- ConsoleLogged in to the Quake AI console
- An AI assistant connected to the Quake AI MCP server. See How to connect AI tools to Quake AI docs.
- A notebook or repository to save into: an Obsidian vault, a Git repo, or a Notion workspace.
What a saved note contains#
Every MCP tool wraps its result in a PortableArtifact envelope. The export and metadata fields give a downstream tool everything it needs to file the result without re-annotation.
| Field | What it holds | How a notebook uses it |
|---|---|---|
export.markdown_preview | Rendered Markdown: YAML frontmatter plus the body | The note content. Obsidian parses the frontmatter as Properties. |
export.obsidian_path_suggestion | A vault-relative path, for example quake-ai/docs/network/concepts/floating-ips.md | The folder and filename to save under |
export.available_formats | The formats the artifact renders as: markdown, json, hcl, yaml | Lets you save HCL for a template or JSON for a data payload |
metadata.quake_ai_docs_url | The canonical docs URL for the source page | A backlink from the note to the live page |
metadata.tags | Tags for the artifact | Tag the note for later filtering |
metadata.generated_at | ISO 8601 timestamp | Records when you pulled the artifact |
The suggested path is always rooted at quake-ai/, so the saved tree drops under an existing notes structure without colliding with your own folders.
| Artifact | Suggested path |
|---|---|
Documentation page (search_docs) | quake-ai/docs/{slug}.md |
IaC template (get_template) | quake-ai/templates/{service}/{template-id}.md |
Launch handoff (prepare_launch) | quake-ai/launch/handoffs/{name}-{request-id}.md |
Save a single result to Obsidian#
Obsidian stores notes as Markdown files with YAML frontmatter, which matches the artifact shape directly. With a connected assistant:
- Ask the assistant to retrieve what you need, for example "Search the Quake AI docs for floating IP setup." The
search_docstool returns adoc_referenceartifact. - Ask the assistant to save the result to your vault at the suggested path: "Save that to my Obsidian vault using the suggested path."
- The assistant writes
export.markdown_previewto a file atexport.obsidian_path_suggestioninside your vault root.
The saved note opens in Obsidian with its frontmatter rendered as Properties and its cross-links resolved as wikilinks. search_docs wires prerequisites and related operations as [[wikilinks]] in the preview, so the note links to the neighbouring concepts once you save those too.
To make this repeatable, add a rule to your assistant so it always files Quake AI artifacts at the suggested path. In Cursor, add it to a project rule; in Claude Code, add it to AGENTS.md:
When a Quake AI MCP tool returns a PortableArtifact, save export.markdown_preview
to the path in export.obsidian_path_suggestion under my vault root.Save to a Git repository or Notion#
The same artifact files into a repository or a Notion workspace.
Git or repo docs. Save export.markdown_preview into your docs/ or adr/ directory. The frontmatter and the metadata.quake_ai_docs_url backlink travel with the file, so a teammate reading the committed note can open the live page. Architecture decisions and template references fit a versioned repo well, since the note changes alongside the code it documents.
Notion. Paste the Markdown into a Notion page, or route it through a Notion MCP server so your assistant creates the page directly. Notion imports the Markdown body and the frontmatter values; use metadata.tags to tag the page and metadata.quake_ai_docs_url for the source link.
Save a whole knowledge bundle with export_okf#
The export_okf tool returns a linked knowledge bundle in the Open Knowledge Format for a service or concept, rather than a single page. The bundle is a set of Markdown concept files plus an index.md, with cross-links intact. An OKF bundle has the same structure as an Obsidian vault: a directory of Markdown files with YAML frontmatter and Markdown links.
- Ask the assistant for a bundle, for example "Export the Quake AI compute knowledge bundle as OKF."
- The tool returns the sub-bundle: the concept files, their
index.md, and the cross-links between them. - Save the bundle into your vault or repository. The assistant writes each concept file at its bundle path and keeps the links resolvable.
Each concept file carries a non-empty type in its frontmatter and a resource pointer to the canonical docs URL, so a saved bundle is a self-describing knowledge subtree you can browse in Obsidian's graph view or commit to a repo.
When your tool does not support MCP#
If your assistant cannot call MCP tools, the documentation is available as plain text and JSON. Save these directly or load them as context.
- Fetch a single page as Markdown by appending
.mdto its docs URL, for examplehttps://docs.quake.ai/docs/network/concepts/floating-ips.md. - Use the corpus and machine-readable surfaces listed on How to connect AI tools to Quake AI docs for the full set of plain-text and JSON URLs.
Related#
- How to connect AI tools to Quake AI docs: set up the MCP server in Cursor, Claude, VS Code, Continue, and Zed.
- AI tools reference: the response envelope, export fields, and the
knowledge-graph.jsonschema in detail. - What the MCP server is and why to use it: what the server returns and when to reach for each tool.
Usage Guidelines
The sample code, software libraries, command line tools, proofs of concept, templates, and other related technology on this page (including any of the foregoing that is provided by Quake AI personnel) is provided to you as Quake AI Content under the Quake AI Customer Agreement, or the relevant written agreement between you and Quake AI (whichever applies). Do not use this Quake AI Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the Quake AI Content (such as sample code) as appropriate for production grade use based on your specific quality control practices and standards. Deploying Quake AI Content may incur Quake AI charges for creating or using Quake AI chargeable resources, such as running Compute instances or storing data in Object Storage. Your use is also subject to the Acceptable Use Policy.
For the full policy, see Usage Guidelines.