Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Local-first MCP server giving AI agents contextual knowledge about the people in your life
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。
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": {
"people-context": {
"command": "uvx",
"args": [
"people-context"
]
}
}
}ターミナルでこれを実行します
claude mcp add people-context -- uvx people-contextプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"people-context": {
"command": "uvx",
"args": [
"people-context"
]
}
}
}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": {
"people-context": {
"type": "stdio",
"command": "uvx",
"args": [
"people-context"
]
}
}
}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。
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7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 JinyangWang27 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昨日です。
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Python (uv)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
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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。
English | 简体中文
Your agent already remembers your codebase. Now it can remember your people.
people-context is a local-first MCP server and CLI that gives AI agents durable memory about the people in your life: who someone is, how you know them, what you last agreed, and how they like to be talked to. One SQLite file on your machine. No account, no cloud, no network calls.
Ask an assistant "how should I approach Priya about the reporting delay?" and it has nothing: it does not know which Priya, that she is your counterpart at a partner org, that you agreed a new deadline last week, or that she prefers a short email over a call. That knowledge lives in your head, your inbox, and a notes file the agent cannot see.
people-context keeps it in one place the agent can query through narrow tools:
It is opinionated about trust: writes are audited, forget is a real delete, sensitive records sit behind an operator-only gate that a prompt cannot open, and ordinary commands never touch the network.
A packaged fictional dataset is the fastest way to see identity resolution, graph traversal, and bounded context without touching real data:
uvx --from people-context pctx demo --reset
The demo always writes its own dedicated database at {XDG_DATA_HOME or ~/.local/share}/people-context/demo.db. It ignores --db, PEOPLE_CONTEXT_DB, the config file, and --reset replaces only that file plus its -wal/-shm companions, so a real database is never read or modified. Seeding writes audited fictional people, handles, affiliations, facts, interactions, and a connected relationship graph, then prints the path-targeted server command and concrete tool calls that use the ids it just created:
Demo database: /home/you/.local/share/people-context/demo.db
Start MCP server: people-context-mcp --db /home/you/.local/share/people-context/demo.db resolve_person {"query": "Amina Hassan"} get_relationship_graph {"person_id": " ", "depth": 2} find_connection {"person_a": " ", "person_b": " "}
Person ids are generated per seed, so the printed values differ from the placeholders above. Start the printed server command in an MCP client and run the printed calls verbatim. See docs/cli.md.
Requires Python 3.11+ and uv. Pick your client; each is one step.
Claude Code
claude plugin marketplace add JinyangWang27/people-context
claude plugin install people-context@people-context-plugins
Restart Claude Code or run /reload-plugins. You get the server plus /people-context:who, /people-context:remember, and /people-context:reminders. Details: docs/claude-code-plugin.md.
Claude Desktop
Download people-context.mcpb from the latest release and open it. Claude Desktop installs the pinned release with its own uv runtime. Details: docs/desktop-and-editors.md.
Codex
codex plugin marketplace add JinyangWang27/people-context
codex plugin add people-context@people-context-plugins
Start a new Codex session. Details: docs/codex-plugin.md.
Cursor, Windsurf, VS Code, or any MCP client
Add the stdio server to your client's MCP config (.cursor/mcp.json, ~/.codeium/windsurf/mcp_config.json, .vscode/mcp.json, ...):
{
"mcpServers": { "people-context": { "command": "uvx", "args": ["--from", "people-context", "people-context"] } } }
Or let the CLI write it: uvx --from people-context pctx setup cursor (also windsurf, vscode, claude-desktop; add --dry-run to preview). VS Code uses a servers key with "type": "stdio". Per-editor snippets: docs/desktop-and-editors.md.
OpenClaw
openclaw plugins install clawhub:openclaw-plugin-people-context
The native plugin talks to the opt-in loopback HTTP server. Details: docs/openclaw-plugin.md.
CLI only
uv tool install people-context
pctx init # seed your own record, optionally import a vCard, then connect a client pctx --help
people-context and people-context-mcp are the server commands; pctx is the human-operated CLI.
Then try, in your agent:
Who is Amina?
Remember that Amina from Open City Lab prefers short emails and hates surprise calls.
What should I know before my meeting with Daniel tomorrow?
The second one is a single remember tool call: the name is resolved, the person is created only if nobody matches, and the affiliation and preference are recorded in one audited transaction. Ambiguous names come back as candidates, never a guess.
Or, without an agent: pctx remember "Amina Hassan" "prefers short emails" --org "Open City Lab" and pctx brief "Amina Hassan". Five worked scenarios live in docs/use-cases.
Prefer a table to a terminal? pctx browse --open opens a local page over the same database:
It binds 127.0.0.1 only, every request needs the per-launch token printed in its URL, and every write goes through the same audited use cases as the CLI and MCP tools. Sensitive records stay hidden unless the operator enables them. It runs until you press Done or Ctrl-C. See docs/cli.md.
| It remembers | It never does |
|---|---|
| Names, nicknames, aliases, and handles | Upload anything, anywhere |
| Relationships with a canonical, extensible vocabulary | Store raw imported emails, chats, or files |
| Organisations, roles, and time-bounded affiliations | Let a model enable sensitive disclosure or full export |
| Durable facts, observations, and traits with evidence | Commit imported or agent-extracted data without your review |
| Concise interaction summaries and a per-person timeline | Log private values or keep a soft-deleted copy after forget |
| Reminders, follow-ups, and your communication philosophy | Make a network request outside pctx reindex --semantic |
people-context | Assistant memory (ChatGPT, Claude) | Memory platforms (Mem0 and similar) | |
|---|---|---|---|
| Where data lives | One SQLite file you own | Vendor account | Vendor platform or your own deployment |
| Works offline | Yes | No | Self-hosted only |
| Knows *people* as first-class records | Identity, relationships, roles, graph, guidance | Free-text notes | Free-text or vector memories |
| Explains a match | Ranked candidates with a reason; ambiguity is surfaced | No | Similarity score |
| Import review gate | Stage, review, commit | n/a | Automatic extraction |
| Deletion | Hard delete plus audit redaction in one transaction | Request to vendor | API delete |
| Backup and move | pctx sync push / pull bundle | n/a | Deployment-specific |
The dated, sourced version with vendor documentation links is in docs/privacy-and-safety.md.
This project executes local Python with the launching user's filesystem permissions. Ordinary MCP discovery excludes elevated sensitive context and full export. Operator-gated tools require process environment flags; models cannot enable them through arguments. Vault export is intentionally CLI-only.
The database is plaintext SQLite by default. On Unix-like systems a new one is created 0600, so other local accounts cannot read it. That is a boundary between accounts, not encryption, so pair it with full-disk encryption or opt into SQLCipher at-rest encryption (uv sync --extra encrypted, key read only from PEOPLE_CONTEXT_DB_KEY). See database file permissions and optional at-rest encryption.
people-context-mcp --http --host 127.0.0.1 --port 8765. Unauthenticated and local-only by design; prefer stdio. See docs/cli.md.uv sync --extra semantic && pctx reindex --semantic downloads a pinned multilingual Model2Vec model once; server startup and search stay cache-only.pctx export-vault --output ~/PeopleVault writes a deterministic, browsable vault, and a read-only Obsidian plugin renders live briefs. See docs/obsidian-plugin.md.pctx import stage SOURCE PATH then review and commit, over email, mbox, vCard, .ics, LinkedIn, Outlook, and WhatsApp exports. Agents can stage extracted candidates the same way. See [docs/import.md](d冒頭だけを表示しています。続きはリポジトリで読めます