Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Local-first, zero-knowledge AI memory across Claude, Cursor, and every MCP client. 0 RTT reads.
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": {
"sovseal-memory": {
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}在终端中运行这条命令
claude mcp add sovseal-memory -- npx -y @sovseal/mcp-server粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"sovseal-memory": {
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}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": {
"sovseal-memory": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@sovseal/mcp-server"
]
}
}
}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
发布者(bobybarack)不是仓库所有者(sovseal);可能是其他人代为上架的
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 0 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(0.3.8)于3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。
Zero-knowledge, local-first AI memory for work you can't send to the cloud.
One private memory across Claude, ChatGPT, Cursor, and every MCP client — plaintext physically never leaves your machine.
@sovseal/mcp-server · @sovseal on npm · Quickstart · How it compares · Changelog
If you work with code, clients, or data you're not allowed to upload — healthcare, legal, fintech, defense, or anything under an NDA — every AI memory option today asks you to break that rule. Platform memory keeps your context on their cloud, in their walled garden, one platform at a time. Cloud memory layers route your raw conversations through third-party servers and extraction APIs.
sovseal takes the other path: all capture, embedding, and recall run on your device. Plaintext never crosses the network. The optional sync tier ships only AES-256-GCM ciphertext — the server cannot read your memories even if it wanted to. And because it speaks MCP and rides a browser extension, it's *one* memory across every AI you use, not six silos.
Cloud-hosted memory layers force a tradeoff between latency, privacy, and cost. Every recall is a 200–800 ms round-trip to someone else's database. sovseal collapses the tradeoff. LanceDB and Transformers.js run *inside* your agent's process.
| Workload | Operation | p50 | p95 | p99 | Network |
|---|---|---|---|---|---|
| 10K records · 1K queries | recall_memory (warm) | 6.1 ms | 10.4 ms | 21.8 ms | 0 RTT |
| Cold start | recall_memory (first call) | ~1.2 s | — | — | 0 RTT |
| Single write | store_memory | 3.8 ms | 7.2 ms | 12.5 ms | 0 RTT (write-behind) |
All benchmarks reproduce with: pnpm --filter @sovseal/mcp-server run bench-v2 (10K pre-seeded memories, 1K sequential queries, CPU-bound ONNX embeddings on commodity hardware).
What makes it fast and private:
sha256(canonicalize(payload)) and fails closed on mismatch.sovseal gives AI assistants and autonomous agents persistent, portable context that you actually own. It drops into any MCP-compatible client, captures from the major chat platforms via a browser extension, and keeps your plaintext where it belongs: on your hardware.
Core Capabilities:
Who it's for:
An honest map, because you'll ask anyway:
| Platform-native memory (ChatGPT / Claude) | Cloud memory layers (mem0, Zep, hosted MCP memories) | sovseal | |
|---|---|---|---|
| Where plaintext lives | Provider's cloud | Provider's cloud, or your servers (self-host = your ops) | Your device only |
| Extraction pipeline | Provider-internal | Typically an LLM API call on your raw text | On-device embeddings; no LLM in the loop |
| Works across platforms | No — each platform is a silo | Yes (via their cloud) | Yes — locally, via MCP + extension |
| Offline | No | No (cloud) / partial (self-host) | Yes |
| Sync model | Provider-controlled | Server reads your data | Server sees ciphertext only |
| Cost per recall | Subscription-gated | API/hosting cost | $0, local compute |
What you give up with sovseal, stated plainly: there's no cloud LLM doing clever extraction on your behalf (by design — that's the leak we exist to prevent), and you are responsible for your own key (see Threat Model). If neither of those matters to you and you live inside one platform, its native memory may be all you need. If they do matter, nothing else in this table does what the right-hand column does.
sovseal exposes one protocol with three delivery shapes. Pick by where your code runs:
| MCP Server | Browser Extension | Node SDK / Self-Hosted | |
|---|---|---|---|
| Best for | Claude Desktop/Code, Cursor, Windsurf, Zed, agent frameworks | ChatGPT, Claude.ai, Perplexity, Grok, Gemini, DeepSeek in the browser | In-process use in a Node/TS service; full data residency |
| Install | npx -y @sovseal/mcp-server | Chrome Web Store + local host installer | npm install @sovseal/sdk |
| Recall latency | 0 RTT (local LanceDB) | 0 RTT (Native Messaging to local engine) | 0 RTT (local LanceDB) |
| Cost | Free (Hobby) | Free (Hobby) | Paid (Starter or above for self-hosted sync) |
The default for AI coding assistants and any agent framework that speaks MCP. One server binary, one config snippet, every client.
Claude Desktop, Cursor, Windsurf, Zed — add to mcp.json or claude_desktop_config.json:
{
"mcpServers": { "sovseal-memory": { "command": "npx", "args": ["-y", "@sovseal/mcp-server"] } } }
One-line install for Claude Code:
claude mcp add sovseal -- npx -y @sovseal/mcp-server
System Prompt Snippet (Claude Desktop / Cursor Project Instructions): To ensure the AI natively uses the memory server, paste this into your custom instructions:
This session has persistent memory via sovseal. At conversation start, check the sovseal://context/recent resource. Whenever the user shares preferences, plans, or personal context, store it via store_memory.
For always-on autonomous agents, switch to HTTP/SSE transport so the sovseal process outlives a single tool invocation:
SOVSEAL_TRANSPORT=sse SOVSEAL_PORT=4040 npx -y @sovseal/mcp-server
For the AI platforms that don't speak MCP. The extension bridges ChatGPT, Claude.ai, Perplexity, Grok, Gemini, and DeepSeek to the same on-device engine over Native Messaging — capture-on-send as you chat, ⌘/Ctrl+M to recall anywhere, with per-site toggles and one-click delete.
Everything the extension captures lives in the same local database the MCP server reads — tell Claude.ai something once, and Claude Code already knows it.
When you're building a backend service and want to manage agent state persistence programmatically, import the Node SDK client. It performs end-to-end AES-256-GCM encryption client-side and replicates checkpoints to a sync endpoint you choose.
npm install @sovseal/sdk
import { AgentStateClient, CryptoService } from "@sovseal/sdk";
const client = new AgentStateClient({ endpoint: "https://your-project.supabase.co/functions/v1/v2-agent-state", apiKey: "sov_proj_your_project_uuid", });
const key = await CryptoService.generateAESKey();
// Client-side AES-GCM encrypted snapshot upload const receipt = await client.snapshot({ key, payload: { agent_id: "agent_a1b2c3", sequence_number: 0, parent_snapshot: null, policy_hash: "0000000000000000000000000000000000000000000000000000000000000000", timestamp: new Date().toISOString(), active_context: { project: "acme-migration", decisions: ["Postgres over Mongo — team expertise", "Cut scope: no SSO in v1"], open_question: "Client prefers staged rollout; confirm dates with their ops lead." } } });
// Restore the latest state snapshot const { receipt: latestReceipt, ciphertextUrl } = await client.restore({ agentId: "agent_a1b2c3", });
The replication endpoint is a Deno edge function — open source, deployable to any Supabase project for full data-residency control.
# From the repo root
supabase functions deploy v2-agent-state supabase db push # applies the agent_state_snapshots schema
export SOVSEAL_ENDPOINT="https:// .supabase.co/functions/v1/v2-agent-state"
Source: supabase/functions/v2-agent-state/.
All of these consume the same MCP server through their first-class MCP support. No sovseal-specific adapter is required:
| Framework | How it consumes MCP |
|---|---|
| ElizaOS | @fleek-platform/eliza-plugin-mcp (config-only, stdio or SSE) |
| Hermes Agent | Native MCP, stdio + remote HTTP |
| CrewAI | mcps=[...] field on the agent |
| LangGraph · LangChain | langchain-mcp-adapters (npm + PyPI) |
| Microsoft Agent Framework | Built-in MCP workbench |
| OpenAI Agents SDK | Native MCPServerStdio / MCPServerSse |
| OpenClaw | Native openclaw mcp consumer |
| Tool | Args | Behavior |
|---|---|---|
store_memory | { content: string } | Embed (384-dim, on-device) → write to local LanceDB → return. Ciphertext replication runs write-behind; nothing blocks. |
| recall_memory | `{ query: string, topK?:
只显示了开头部分;其余内容请在仓库中阅读