Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Token-lean memory for AI agents: a knowledge graph searched cheaply. Drop-in for server-memory.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
MEMORY_FILE_PATH必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"memory-lean": {
"command": "npx",
"args": [
"-y",
"memory-lean"
],
"env": {
"MEMORY_FILE_PATH": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add memory-lean --env MEMORY_FILE_PATH=your-value -- npx -y memory-lean動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"memory-lean": {
"command": "npx",
"args": [
"-y",
"memory-lean"
],
"env": {
"MEMORY_FILE_PATH": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"memory-lean": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"memory-lean"
],
"env": {
"MEMORY_FILE_PATH": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
MEMORY_FILE_PATH envこの設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント zamansheikh で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(1.5.0)がレジストリに届いたのは21 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
memory-lean
Long-term memory for AI coding agents that doesn't burn the context window.
A knowledge graph your agent searches cheaply, and a web UI where you can see and edit all of it.
Quick start · Web UI · How it works · Tools · Setup for 12 agents · Contributing
memory-lean is an MCP server that gives Claude Code, Codex, Cursor, MiMo Code and any other MCP client a memory that lasts between sessions: which projects exist, what depends on what, which version shipped, what is still pending, and which rules were learned the hard way. It is a drop-in replacement for the reference memory server (@modelcontextprotocol/server-memory), with the same file and tool names, but its answers are about 40 times smaller.
About 40× smaller answers. Search returns a ranked list of names and the lines that matched, not every entity in full, so the agent can afford to check its memory before every task.
A web UI for people. See the whole graph grouped by type, follow relations, and add, edit or delete anything. Agent writes show up live.
Drop-in replacement. Same memory.jsonl file and the same nine tools as the reference server. Switch in, and switch back whenever you like.
Works with every agent. Copy-paste setup for Claude Code, MiMo Code, Codex, Cursor, Copilot, Gemini CLI, Zed, JetBrains and more, plus the instructions that teach the agent to use it.
Stays small by itself. Short facts, a cap per entity, and an archive for the overflow, so the graph never grows into a wall of text.
Private and safe. Plain local files, daily backups, a write lock for parallel sessions, and no network access. One server file, zero dependencies.
Measured on a real graph of 237 entities, 355 relations and 1,160 facts (tokens ≈ characters ÷ 4):
| Call | Reference server | memory-lean | |
|---|---|---|---|
read_graph | ~77,800 tokens | ~2,000 tokens | 40× smaller |
search_nodes, average of 5 common words | ~31,000 tokens | ~770 tokens | 40× smaller |
A narrow search that matches one or two entities saves less, because there is little to trim. To measure your own graph, run node tools/bench.mjs from a clone; it is read-only and prints sizes, never content.
Claude Code: install the plugin. It adds the server, the instructions as a skill, a short reminder at the start of each session, and /memory-ui.
/plugin marketplace add zamansheikh/memory-lean
/plugin install memory-lean@memory-lean
Any other agent: add the server to its MCP config, then give it the instructions.
{
"mcpServers": { "memory": { "command": "npx", "args": ["-y", "memory-lean"] } } }
npx -y memory-lean --protocol >> AGENTS.md # into the rules file your agent reads
Just looking? Open the web UI on a made-up example graph:
npx -y memory-lean --ui --demo
Setup for each agent
| Agent | Server config | Instructions |
|---|---|---|
| Claude Code | plugin | included in the plugin |
| Xiaomi MiMo Code | mimocode.jsonc | skill or AGENTS.md |
| opencode | opencode.json | AGENTS.md |
| OpenAI Codex CLI | codex mcp add | AGENTS.md |
| Cursor | .cursor/mcp.json | AGENTS.md or a rule |
| VS Code (Copilot) | .vscode/mcp.json | copilot-instructions.md |
| Gemini CLI | settings.json | GEMINI.md |
| Windsurf | mcp_config.json | a rule |
| Cline | cline_mcp_settings.json | .clinerules/ |
| Zed | settings.json | AGENTS.md or .rules |
| JetBrains IDEs | AI Assistant settings | a rule or guidelines |
| Claude Desktop | claude_desktop_config.json | project instructions |
The graph is created on the first write at ~/.claude/memory-graph/memory.jsonl, whichever agent writes it, so all your agents share one memory. Set MEMORY_FILE_PATH to keep it somewhere else.
npx -y memory-lean --ui
This opens your memory in the browser. Everything an agent can do, you can do here:
Follow the connections. Select an entity to see its facts and relations. Find anything. Search names, types and facts at once.
Edit in place. With the same 300-character limit the agents have. Light or dark. It follows your system, or pick one.
The page runs on your machine only (127.0.0.1) and needs the one-time key in the link it prints, so other websites cannot read or change your memory. Nothing is uploaded anywhere.
The reference server answers a search with every matching entity in full, as pretty-printed JSON. memory-lean answers with a ranked list of names and the lines that matched:
> search_nodes { "query": "deploy" }
57 match "deploy", top 10 shown (narrow the query or raise limit). open_nodes for full entities.
The agent then opens only what it needs:
> open_nodes { "names": ["shop-backend"] }
shop-app -talks_to-> shop-backend PENDING shop-backend 2.4.0 -blocks-> shop-app
| Limit | What it means |
|---|---|
| Small answers | search_nodes returns at most 10 names with snippets, read_graph returns an index of names, and only open_nodes returns full entities. |
| Short facts | An observation longer than 300 characters is rejected, with a message telling the agent to split it or put the detail in the repo. |
| A cap per entity | An entity keeps 15 observations. Past that, the oldest dated ones move to archive/ .md. Nothing is deleted: they can be listed and restored, and undated facts (the identity facts) always stay. |
| Search that narrows | Every word must match somewhere in the entity, so adding a word narrows the result. The reference server looks for the query as one exact phrase. |
| Safeguard | What it means |
|---|---|
| Safe to share | Writers take a lock file, so several agent sessions can use one graph without overwriting each other. Every write replaces the file atomically. |
| Daily backups | A copy goes to backups/ once a day; the last 7 are kept. |
| Damaged lines are kept | A line that cannot be read is moved to memory.jsonl.unreadable on the next write and reported, never silently dropped. |
| Plain files | The graph is JSON lines, archives are Markdown, backups are copies. You can read, grep and edit all of it by hand. |
| Tool | What it returns |
|---|---|
search_nodes | Ranked list of entity names with counts and up to two matching snippets each. Every word must match the name, type, an observation, or the type of a relation touching the entity. |
open_nodes | The full entities you name, as compact text, with every relation touching them and their archive count. Unknown names come back with "did you mean" suggestions. |
read_graph | An index: entity names grouped by type, with observation counts. Never the observations. |
create_entities | Creates entities; existing names are skipped. |
create_relations | Creates relations between existing entities; duplicates are skipped. |
add_observations | Adds facts to an entity, enforcing the length limit and the per-entity cap. |
delete_observations | Removes observations by exact text. |
delete_relations | Removes specific relations. |
delete_entities | Removes entities and every relation touching them. |
rename_entity | Renames an entity, keeping its observations, relations and archive. *Not in the reference server.* |
| archived_observations | Lists what was archived for an entity, optionally filtered, and restores chosen fa
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