Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Local-first MCP server giving AI agents contextual knowledge about the people in your life
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"people-context": {
"command": "uvx",
"args": [
"people-context"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add people-context -- uvx people-contextPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"people-context": {
"command": "uvx",
"args": [
"people-context"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"people-context": {
"type": "stdio",
"command": "uvx",
"args": [
"people-context"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub JinyangWang27, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (1.5.0) llegó al registro ayer.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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](dSolo se muestra el principio; lee el resto en el repo