Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Token-lean memory for AI agents: a knowledge graph searched cheaply. Drop-in for server-memory.
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。
MEMORY_FILE_PATH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": {
"memory-lean": {
"command": "npx",
"args": [
"-y",
"memory-lean"
],
"env": {
"MEMORY_FILE_PATH": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add memory-lean --env MEMORY_FILE_PATH=your-value -- npx -y memory-lean运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"memory-lean": {
"command": "npx",
"args": [
"-y",
"memory-lean"
],
"env": {
"MEMORY_FILE_PATH": "your-value"
}
}
}
}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": {
"memory-lean": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"memory-lean"
],
"env": {
"MEMORY_FILE_PATH": "your-value"
}
}
}
}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。
MEMORY_FILE_PATH env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6日
注册名称已通过 GitHub 账户 zamansheikh 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(1.5.0)于21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。
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
只显示了开头部分;其余内容请在仓库中阅读