Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Search, read and build your Filamental knowledge graph. Local-first: notes stay on your computer.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"filamental": {
"command": "npx",
"args": [
"-y",
"filamental-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add filamental -- npx -y filamental-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"filamental": {
"command": "npx",
"args": [
"-y",
"filamental-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"filamental": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"filamental-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 Scottnine 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.2.17)于9天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.
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.
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.
| Tool | What it does |
|---|---|
get_structure_report | A 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_context | One node's notes plus its neighbourhood, inlined as one readable markdown document. dry_run sizes it first |
find_path | The shortest chain of connectors between two nodes, by name or UUID, with how each hop reads |
search_nodes | Full-text search across names, notes and property values, with an optional field filter that also works on its own |
get_node | One node's full record, notes included |
get_connections | Every connector on a node, stated from that node's point of view (see Arrow direction) |
get_subgraph | Every node and connector within up to 3 hops of a node |
get_project_info | Node and connector counts, and the classification and connector type names |
list_node_types | The project's classifications (entity types), with their colours and settings |
list_connector_types | The project's connector types, with their colours, directions and weights |
| Tool | What it does |
|---|---|
create_node | Create a node: writes its markdown file and updates the index |
update_node | Change a node. Omitted fields stay as they are; a properties or relationships you pass replaces the whole set |
delete_node | Delete a node and its file |
create_edge | Connect two nodes |
delete_edge | Remove a connector |
extract_section | Move 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_section | Fold 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.
| Tool | What it does |
|---|---|
read_skill_guide | The full guide to designing a Filamental structure. The server sends the essentials when it connects, so this is for depth |
read_format_reference | The 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.
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:
| Field | Meaning |
|---|---|
node | The node you asked about |
other | The node at the far end |
direction | Where the arrowhead is drawn, as seen from node |
stored_on | Which 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.
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)
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.
| filamental-mcp | Filamental app | Index schema |
|---|---|---|
| 0.2.6 and later | 0.3.0 and later | v6 |
| 0.2.0 – 0.2.5 | 0.2.x | v5 |
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.
MIT. The Filamental desktop app itself is proprietary; its terms are at filamental.space/terms.