Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Local-first MCP server giving AI agents contextual knowledge about the people in your life
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"people-context": {
"command": "uvx",
"args": [
"people-context"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add people-context -- uvx people-context프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"people-context": {
"command": "uvx",
"args": [
"people-context"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"people-context": {
"type": "stdio",
"command": "uvx",
"args": [
"people-context"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 JinyangWang27 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.5.0)은 어제 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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](d앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요