New to this? Start with AI Basics: Side-by-Side, a six-step walkthrough for going from a blank project to a populated graph using nothing but copy and paste. Come back here once you want to go deeper: live connections, persistent skills, and the full prompt library.
There are five ways to work with AI in Filamental. Which one you reach for depends on which AI you use, how deep the task is, and whether your AI can see your machine.
Skills are not a sixth method, they're the briefing. Every route needs the AI to understand what Filamental is and how a node file is put together. Filamental AI and MCP hand that over for you automatically, with nothing to install. The other three need you to supply it, which is what the skill files are for. What We Tell Your AI shows you the exact text either way.
A rough rule: if your AI can reach your machine, use MCP or folder access. If it can't, use Copy World or Mermaid import with a skill loaded. Filamental AI works regardless, because the app does the reaching for you.
Click the AI button in the top bar. Paste an API key from whichever provider you already use, Claude, GPT, Gemini, DeepSeek, Kimi, Qwen, or similar, and Filamental works out which one it is and connects you. Nothing else to install, no separate app, no Node.js.
It gets the same live read/write access to your open project that MCP gives Claude: search nodes, follow connections, create and edit content, define whole category and connector vocabularies, all from the chat window. Attach a PDF, image, or Word file straight to a message.
Filamental never sees or stores your key or your conversation, both stay strictly between you and your chosen provider. And to be clear about what this is: Filamental doesn't have its own AI, this is a plain wrapper around whichever model you connect. The header always says exactly which one, "Connected to: Claude" or whichever you picked, nothing blended or implied.
Multiple models: connect more than one and switch between them from the dropdown at the top of the chat, handy for a second opinion or a cheaper model for quick questions.
If you're on GPT or Gemini and want a live, no-copy-paste connection with the same reach MCP gives Claude, this is it.
If you specifically live in Claude Desktop, Claude Code, Cursor or LM Studio rather than Filamental's own chat window, connect via MCP instead. Same live read/write access, just from your AI's window rather than Filamental's.
What the AI is given. The briefing arrives in three layers and none of them need installing. The essentials land the moment you connect: what nodes, types and connectors are, how relationships work, and the conventions that keep a structure readable. Beyond that the AI can pull the full skill guide and the complete file format spec on demand, but only when a task actually calls for them. It's a better arrangement than pasting a skill in by hand, because nothing is spent on detail the job doesn't need.
Which world does Claude see? Whichever one is open/you last opened in Filamental, that's the reference point. (Filamental doesn't technically need to be running but in practice you'll have it open anyway.)
How it differs from Filamental AI: functionally near-identical, the real difference is just which window you're typing in.
What the AI can do: You can have a full conversation about a topic and then say "turn this into a Filamental project folder" and it will do exactly that. It's exactly how we created the demos on the website. Come back later, ask it to read the folder again, and it's fully briefed in seconds, with a full relational understanding.
Setup (Claude Desktop):
Filamental handles the path resolution. The connection follows whichever world you have open, no restart needed if you switch worlds later.
Claude Code: works the same way, but configured per-project rather than globally. Create .mcp.json at the root of your project folder:
{
"mcpServers": {
"filamental": {
"command": "node",
"args": [
"--no-warnings",
"/absolute/path/to/filamental-mcp/dist/index.js",
"--vault",
"/absolute/path/to/your/vault"
]
}
}
}Copy the exact paths for your machine from Settings > AI Integrations > Manual setup. Claude Code picks up .mcp.json automatically when it starts in that folder. The --vault argument pins the connection to a specific vault, there's no auto-follow here, it's project-scoped by design. You can commit .mcp.json to version control if you want the whole team on the same connection.
Cursor: the same JSON config works here too (~/.cursor/mcp.json, or .cursor/mcp.json inside a project).
LM Studio: supported since LM Studio 0.3.17, which acts as an MCP host. Add Filamental to its mcp.json using the same paths from Settings > AI Integrations > Manual setup. Worth knowing that the protocol working is not the same as it working well, a smaller local model has to call tools accurately and repeatedly to build a structure, and they vary enormously at this. Try it on a small project first.
Open WebUI: not directly. Its MCP support is HTTP-only by design, since it runs as a web app rather than a local process, and Filamental's server talks over stdio. It can be bridged with a proxy such as mcpo, but that's a self-assembly job and we don't support it.
Requirements: Claude Desktop, Cursor, Claude Code or LM Studio; Node.js 22 or later; Filamental v0.2.4 or later. Filamental AI above has none of these requirements, reach for that first unless you specifically live in one of these tools already.
For AI tools that read files on your machine directly: Claude Code, Cowork, or any agent with filesystem access.
Rather than connecting to Filamental at all, you point the AI at the project folder and let it read your notes as what they are, plain markdown files on disk. Install the two skill files below so it knows the format, and it can read your whole structure, reason across it, and write properly formed new nodes straight back into the folder. Hit refresh and they appear.
This is the method that turns Filamental into a genuine second brain rather than a graph you consult. The AI isn't visiting your structure through a window, it's working inside the folder alongside everything else you keep there.
Why you'd choose this over MCP:
Why you'd choose MCP over this:
Requirements: an AI with file access to your machine, and both skill files installed.
Skills are how you brief an AI that can't be briefed automatically. If you're on Filamental AI or MCP, the briefing is already handed over and there's nothing to install. If you're using folder access, Copy World or Mermaid import, this is the piece that teaches your AI what it's looking at.
Reach for a skill if you're using ChatGPT, Gemini, or Claude.ai (the web version), none of which support MCP. A skill is a prewritten briefing you install once in your AI. It teaches the AI how Filamental works: the structure, node format, and type system. Once installed, pair it with a Copy World snapshot (below) and almost any AI can work with your vault nearly as well as Claude does via MCP.
The skill files are also just readable documents. If you want to see how Filamental describes itself to an AI, or you'd rather write your own briefing, download them and read them. What We Tell Your AI shows the exact text sent to connected assistants.
Recently, the major AI platforms agreed to Claude's skill standard, so installation is fairly painless everywhere now. A "plugin" in an AI platform's own discovery menu is just a formal listing of skills, ours are already there to download that way if your platform supports it, as an alternative to manual install.
Install: Go to Customise > Skills > New Skill, then copy-paste the text from the two skill files.
The Filamental skill is two parts:
filamental_SKILL.md, the main briefing: working modes, scaffolding, session building, format compliance rules.filamental-format-reference, a companion covering the complete node file format spec, UUID rules, filename conventions, and the integrity checklist.In Cowork both install as separate skills and work together automatically. Elsewhere, both are distributed as files, install both for full capability. The main skill alone is enough for reading and analysis; the format reference is required whenever the AI is writing or generating node files.
What happens when the skill is active: the AI reads your .filamental/ config to learn your type vocabulary, reads whatever you've given it access to, then gives you a brief orientation and asks what you want to do. From there: gap analysis, new nodes, a briefing, a whole new project from scratch, or any question about the structure.
With Cowork or Claude Code: install both skills, then point the AI at your folder. See Folder Access above, that's the route this combination unlocks and it's the most capable one on this page.
With Claude.ai: paste SKILL.md into Project Instructions. At the start of each conversation, use the broadcast button (below) to export your snapshot and paste it in.
With any other AI: paste SKILL.md as a system prompt at the start of your conversation, then share your project snapshot.
Click the broadcast icon in the bottom bar and your entire world, every node, connection, and type definition, is copied to your clipboard as structured text. Paste it into any AI and start talking. Quick and easy, and a good way to "one-shot" a conversation without any install step.
Paste it in with an opener like:
Here is my Filamental knowledge graph. I will follow up with specific questions.
[paste your world snapshot here]Tip for ongoing work: if you're coming back to the same world across sessions, create a Claude Project and paste your snapshot into the project instructions. Claude keeps that context persistently, just re-export and update the instructions when your world changes significantly.
A complete route in its own right, and the one that needs least from your AI. Talk a subject through in any chat tool, ask for the result as a Mermaid diagram, then import that diagram as a structure. No connection, no skill, no file access. Every AI worth using can produce Mermaid.
It's the fastest way from a conversation you've already had to something you can navigate, and it pairs well with the others: import the skeleton this way, then use one of the live routes to fill in the notes.
Conversation to Graph: append this to the end of any AI conversation to turn the discussion itself into a structure, no need to re-describe it.
Convert this conversation into a Mermaid flowchart I can import into a knowledge graph tool.
Rules:
- Opening line must be: flowchart TD
- Node IDs must use alphanumeric characters and hyphens only (e.g. payment-api not "Payment API")
- Node labels go inside brackets: nodeID[Label Here]
- Use [square brackets] for most nodes
- Use (round brackets) for processes or steps
- Use {curly brackets} for decisions or branch points
- Use ((double brackets)) for key goals or outcomes
- Connect nodes with --> for directed flow, --- for undirected, <--> for bidirectional
- Label edges where the relationship has a clear name: A -->|feeds into| B
- Aim for 10 to 20 nodes. Collapse minor details and keep the concepts that matter most
- Do not include subgraph, style, classDef, or click lines
Output only the Mermaid code block. No explanation before or after it.Create a structure from scratch: for a topic you haven't discussed yet. Nine times out of ten, just saying "turn this conversation into a mermaid chart code" is enough. For more control:
Generate a Mermaid flowchart of [describe your topic here].
Rules:
- Opening line must be: flowchart TD
- Node IDs must use alphanumeric characters and hyphens only (e.g. market-research not "Market Research")
- Node labels go inside brackets: nodeID[Label Here]
- Use [square brackets] for most nodes
- Use (round brackets) for processes or steps
- Use {curly brackets} for decisions or branch points
- Use ((double brackets)) for key goals or outcomes
- Connect nodes with --> for directed flow, --- for undirected, <--> for bidirectional
- Label edges where the relationship has a name: A -->|depends on| B
- Aim for 12 to 20 nodes. Focus on key concepts, not exhaustive detail
- Do not include subgraph, style, classDef, or click lines
Output only the Mermaid code block. No explanation before or after it.Replace the bracketed description with something specific, for example "the components of a SaaS startup's go-to-market strategy," or "how a payment transaction flows from customer to bank."
To import either result: Bottom toolbar > + button > Insert Mermaid diagram > paste > Build. The wizard asks you to map each shape to a node type, create new ones on the spot or assign to existing ones. Node titles are capped at 200 characters, if a Mermaid label is longer, that node will fail to import, shorten it first.
Do this after a Copy World export (above).
Gap Analysis: ask Claude what's missing.
Looking at the knowledge graph I have shared with you, please identify:
1. Important concepts that appear to be missing from the graph entirely
2. Nodes that seem underdeveloped: isolated with few connections, or lacking in related ideas
3. Connections that are implied by the existing structure but not explicitly drawn
4. Any areas where the graph feels unbalanced: too much detail in one area, too little in another
For each finding, suggest a concrete action: a node to add, a connection to draw, or a note to write.
Keep your response structured and specific to the nodes and connections in this graph. Do not make generic suggestions that could apply to any knowledge graph.Expand a Node: ask Claude to develop one node further.
Looking at the node "[node name]" in the knowledge graph I have shared:
1. Suggest 5 new nodes that would meaningfully extend or connect to this one
2. For each suggestion provide:
- A short node name suitable as a file name
- Which entity type it should be, using the types defined in my graph
- One sentence describing what it represents
- How it should connect to "[node name]": the connection type and direction
Focus on genuine gaps in the current graph. Do not suggest nodes that are already there or that are close variations of what exists.id: on one of the other generated nodes.No direct integration yet. Workaround: download the doc as a file, then drop it into the folder or use the Insert menu (see Graph). Google doesn't play well with local files and wants your data in their cloud, we'll figure it out eventually.
A useful external resource for open-source intelligence work: osintframework.com. We've been told Filamental pairs well with Spiderfoot (OSINT automation), similar-looking tools, different jobs.
Still stuck? Email [email protected].