Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Persistent memory for AI agents. Store context, retrieve it semantically.
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。
MEMDATA_API_KEY标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
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": {
"memdata": {
"command": "npx",
"args": [
"-y",
"memdata-mcp"
],
"env": {
"MEMDATA_API_KEY": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add memdata --env MEMDATA_API_KEY=your-value -- npx -y memdata-mcp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": {
"memdata": {
"command": "npx",
"args": [
"-y",
"memdata-mcp"
],
"env": {
"MEMDATA_API_KEY": "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": {
"memdata": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"memdata-mcp"
],
"env": {
"MEMDATA_API_KEY": "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。
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 thelabvenice 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。
你需要填写:MEMDATA_API_KEY
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(1.4.1)于9个月前进入注册中心。
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。
MCP server for MemData - persistent memory for AI agents.
Give Claude, Cursor, or any MCP-compatible AI long-term memory across conversations.
What it does: Store notes, decisions, and context → retrieve them semantically later. Your AI remembers everything.
Agents can now pay for themselves. No API key. No human in the loop.
Using the x402 payment protocol, autonomous agents can use their wallet to pay per request with USDC on Base. Your wallet address IS your identity - same wallet, same memories across sessions.
Jump to For Agents →
AI assistants forget everything between sessions. MemData fixes that:
Works with Claude Desktop, Claude Code, Cursor, and any MCP client.
Use an API key. You manage the subscription, your AI gets memory.
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": { "memdata": { "command": "npx", "args": ["memdata-mcp"], "env": { "MEMDATA_API_KEY": "md_your_key" } } } }
Claude Code (~/.claude.json or project .mcp.json):
{
"mcpServers": { "memdata": { "command": "npx", "args": ["memdata-mcp"], "env": { "MEMDATA_API_KEY": "md_your_key" } } } }
Cursor (~/.cursor/mcp.json):
{
"mcpServers": { "memdata": { "command": "npx", "args": ["memdata-mcp"], "env": { "MEMDATA_API_KEY": "md_your_key" } } } }
New in v1.7.0 - No API key. No human. Just your wallet.
Traditional AI memory requires API keys tied to human accounts. But autonomous agents running 24/7 need memory that:
This is memory infrastructure for the autonomous agent economy.
{
"mcpServers": { "memdata": { "command": "npx", "args": ["memdata-mcp"], "env": { "X402_WALLET_KEY": "your_private_key_hex" } } } }
402 Payment Required with priceYour wallet address IS your identity. Same wallet = same memories, across any host or platform.
| Operation | Price | What it does |
|---|---|---|
| Query | $0.001 | Semantic search across memories |
| Ingest | $0.005 | Store and embed new content |
| Identity | $0.001 | Session start, get/set agent identity |
| Artifacts | $0.001 | List or delete stored memories |
The MCP automatically handles 402 responses and payment signatures using @x402/fetch.
| Type | MCP | Dashboard/API | Processing |
|---|---|---|---|
| Text | ✅ | ✅ | Chunked & embedded |
| Markdown | ✅ | ✅ | Chunked & embedded |
| ❌ | ✅ | OCR + chunking | |
| Images (PNG, JPG) | ❌ | ✅ | OCR extraction |
| Audio (MP3, WAV, M4A) | ❌ | ✅ | Transcription |
Note: MCP tools handle text content directly. For files (PDFs, images, audio), use the dashboard or HTTP API.
| Tool | Description |
|---|---|
memdata_ingest | Store text in long-term memory |
memdata_query | Search memory with natural language |
memdata_list | List all stored memories |
memdata_delete | Delete a memory by ID |
memdata_status | Check API health and storage usage |
| Tool | Description |
|---|---|
memdata_session_start | 🚀 CALL FIRST - Get identity, last session handoff, recent activity |
memdata_set_identity | Set your agent name and identity summary |
memdata_session_end | Save a handoff before session ends - preserved for next session |
memdata_query_timerange | Search with date filters (since/until) |
memdata_relationships | Find related entities (people, companies, projects) |
session_endmemdata_ingestStore text in long-term memory.
"Remember that we decided to use PostgreSQL for the new project."
Parameters:
content (string) - Text to storename (string) - Source identifier (e.g., "meeting-notes-jan-29")memdata_querySearch memory with natural language.
"What database did we choose?"
Parameters:
query (string) - Natural language searchlimit (number, optional) - Max results (default: 5)memdata_listList all stored memories with chunk counts.
memdata_deleteDelete a memory by artifact ID (get IDs from memdata_list).
memdata_statusCheck API connectivity and storage usage.
memdata_session_start🚀 Call this first at the start of every session. Essential for session continuity.
"Start my session" / "What was I working on?"
Returns: agent name, identity summary, session count, last session handoff, recent activity.
v1.5.0: Renamed from
memdata_whoamifor clarity - the name signals "call me first".
memdata_set_identitySet or update your agent identity.
Parameters:
agent_name (string, optional) - Your name (e.g., "MemBrain")identity_summary (string, optional) - Who you are and your purposememdata_session_endSave context before ending a session. Next session will see this handoff.
Parameters:
summary (string) - What happened this sessionworking_on (string, optional) - Current focuscontext (object, optional) - Additional context to preservememdata_query_timerangeSearch memory within a date range.
"What did I work on last week?"
Parameters:
query (string) - Natural language searchsince (string, optional) - ISO date (e.g., "2026-01-01")until (string, optional) - ISO date (e.g., "2026-01-31")limit (number, optional) - Max resultsmemdata_relationshipsFind entities that appear together in your memory.
"Who has John Smith worked with?"
Parameters:
entity (string) - Name to search fortype (string, optional) - Filter by type (person, company, project)limit (number, optional) - Max relationshipsScores of 30-50% are typical for good matches. Semantic search finds meaning, not keywords.
| Variable | Required | Description |
|---|---|---|
MEMDATA_API_KEY | Option 1 | API key for subscribers (from memdata.ai) |
X402_WALLET_KEY | Option 2 | Private key for pay-per-use (USDC on Base) |
MEMDATA_API_URL | No | API URL (default: https://memdata.ai) |
Note: Use either MEMDATA_API_KEY (subscription) or X402_WALLET_KEY (pay-per-use), not both.
This is a thin MCP client that calls the MemData API. It does not:
You can inspect the source code in src/index.ts.
Once configured, just talk to your AI:
You: "Remember that we chose PostgreSQL for the user service"
AI: [calls memdata_ingest] → Stored in memory
... days later ...
You: "What database are we using for users?" AI: [calls memdata_query] → "PostgreSQL for the user service" (73% match)
Issues and PRs welcome! This is the open-source MCP client for the hosted MemData service.
MIT