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Filamental

by Scottnineversion 0.2.17i★ –iRuns on your computer
Registry nameio.github.Scottnine/filamental

Install

Overview

Description from the maker (original English)

Search, read and build your Filamental knowledge graph. Local-first: notes stay on your computer.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "filamental": {
      "command": "npx",
      "args": [
        "-y",
        "filamental-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add filamental -- npx -y filamental-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "filamental": {
      "command": "npx",
      "args": [
        "-y",
        "filamental-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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "filamental": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "filamental-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.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

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.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Scottnine, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 7270 servers in this category
  • Published to the registry more recently than 80% of the other 7270 servers in this category
  • Basic checks equal to or better than 100% of the other 7270 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Filamental safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.17) reached the registry 9 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
Install

README from the maker

Open the README

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.

filamental-mcp

The Model Context Protocol server for Filamental. It lets Claude and other AI apps search, read and build the knowledge graph in your Filamental project: the same markdown files the app shows you, so every change appears in the app as it happens.

The server runs on your computer, works whether Filamental is open or closed, and makes no network requests of its own.

Requires the Filamental desktop app, with the project opened in it at least once, and Node.js 22 or later.


Setup

From Filamental

Open Settings › AI. Under Connect an AI app, Connect sets up Claude Desktop in one click. For any other app, Show setup beside Other AI apps gives the exact block for that app, with the paths for your computer filled in.

By hand

Add this to your AI app's MCP settings file (claude_desktop_config.json, .mcp.json for Claude Code, .cursor/mcp.json and so on):

{

"mcpServers": { "filamental": { "command": "npx", "args": ["-y", "filamental-mcp"] } } }

No path is needed. The server works on whichever project Filamental has open, and follows you when you open another, with no restart. To pin it to one project instead, add "--project", "/absolute/path/to/your/project" to args.


Tools

Orient and read
ToolWhat it does
get_structure_reportA short orientation to the whole project: its classifications and connectors, the most connected nodes, the load-bearing ones, separate groups, and nodes that are unconnected or have no notes
get_contextOne node's notes plus its neighbourhood, inlined as one readable markdown document. dry_run sizes it first
find_pathThe shortest chain of connectors between two nodes, by name or UUID, with how each hop reads
search_nodesFull-text search across names, notes and property values, with an optional field filter that also works on its own
get_nodeOne node's full record, notes included
get_connectionsEvery connector on a node, stated from that node's point of view (see Arrow direction)
get_subgraphEvery node and connector within up to 3 hops of a node
get_project_infoNode and connector counts, and the classification and connector type names
list_node_typesThe project's classifications (entity types), with their colours and settings
list_connector_typesThe project's connector types, with their colours, directions and weights
Write
ToolWhat it does
create_nodeCreate a node: writes its markdown file and updates the index
update_nodeChange a node. Omitted fields stay as they are; a properties or relationships you pass replaces the whole set
delete_nodeDelete a node and its file
create_edgeConnect two nodes
delete_edgeRemove a connector
extract_sectionMove a heading's section out of a node into a node of its own, leaving a [[wikilink]] and a connector behind. dry_run previews it
inline_sectionFold a node's content back into another: the inverse of extract_section. dry_run previews it

The content is moved, never copied, so exactly one copy of any text survives.

Guides
ToolWhat it does
read_skill_guideThe full guide to designing a Filamental structure. The server sends the essentials when it connects, so this is for depth
read_format_referenceThe exact on-disk format of node files and the .filamental/ folder

Every tool carries MCP annotations (readOnlyHint, destructiveHint), so your AI app can tell the read-only tools from the ones that change or delete content.

On Filamental's free plan a project holds 20 nodes, not counting bridges, and that includes nodes an AI creates: create_node says so when a project is full. Pro has no limit.


Arrow direction

A connector's direction is one of none, outgoing, incoming or bidirectional. Nothing else is accepted, and an unrecognised value is rejected rather than stored.

On writes (create_edge, create_node, update_node) direction is stated relative to source → target: outgoing draws the arrowhead at the target, incoming draws it back at the source, bidirectional draws both, none is a plain line.

On reads (get_connections) direction is instead stated relative to the node you asked about, because that is what the user sees on screen:

FieldMeaning
nodeThe node you asked about
otherThe node at the far end
directionWhere the arrowhead is drawn, as seen from node
stored_onWhich node's file holds the relationship

This matters because which end of a connector is stored as source is simply whichever end the user happened to drag from, and it's invisible on the graph: an undirected connector looks the same either way round. So the same arrow reads as outgoing from one end and incoming from the other, and get_connections flips it for you. Filtering with direction: "outgoing" gives the edges whose arrow points *away from* the node you asked about. A bidirectional edge matches both outgoing and incoming, since it genuinely points both ways; undirected matches only edges with no arrow.

Use stored_on only if you're editing the underlying markdown file directly. It says nothing about what the arrow does.


CLI options

filamental-mcp                              Follow the project Filamental has open

filamental-mcp --project Pin to the project at filamental-mcp --project --db Also override the SQLite index path (for testing)


How it works

Every node in a Filamental project is a markdown file with YAML front matter, inside the project folder. The app also keeps a SQLite index of each project for fast search and traversal, stored in the app's own settings folder rather than in the project.

The server opens that index. Read tools query it; write tools update the markdown file and the index together, and keep any front-matter fields they don't own (Obsidian's tags and aliases, say) exactly where they were.


Compatibility

filamental-mcpFilamental appIndex schema
0.2.6 and later0.3.0 and laterv6
0.2.0 – 0.2.50.2.xv5

On a schema mismatch the server keeps working where it can, since the index is disposable, and annotates any failing call with which side to update.


Licence

MIT. The Filamental desktop app itself is proprietary; its terms are at filamental.space/terms.

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