Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Shared, project-aware memory for Claude Code, Codex, and other agents with human review.
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": {
"global-agent-memory": {
"command": "uvx",
"args": [
"global-memory-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add global-agent-memory -- uvx global-memory-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"global-agent-memory": {
"command": "uvx",
"args": [
"global-memory-mcp"
]
}
}
}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": {
"global-agent-memory": {
"type": "stdio",
"command": "uvx",
"args": [
"global-memory-mcp"
]
}
}
}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 ozankasikci, 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 (0.1.6) llegó al registro hace 4 meses.
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
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.
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.
Local-first, project-aware, durable memory for Claude Code, Codex, and other
MCP-compatible agents.
Global Agent Memory gives multiple coding agents one shared, reviewable memory without handing control of your knowledge base to a hosted service. Markdown files are canonical, a hybrid local MCP runtime is the public agent interface, and the dashboard lets a human approve, edit, protect, or remove what agents remember. Agent commands work without a background server. The authenticated localhost server starts on demand for the dashboard and can optionally run continuously for live file watching and shared embedding work.
One Vault. Multiple agents. Human-controlled memory.
Quick start · Obsidian Vault · Dashboard · How it works · Security · MCP contract · Documentation
Coding agents are useful inside a session, but important context is often lost between sessions or fragmented across individual clients. Global Agent Memory provides a durable layer for knowledge such as:
Agents propose memories as candidates. A human reviews them before they become durable, controls their visibility, and can later update, supersede, archive, or hard-delete them.
| Approach | Shared across agents | Human-reviewable | Project-aware | Owner-controlled access | Portable source of truth |
|---|---|---|---|---|---|
CLAUDE.md / AGENTS.md | Limited | ✓ | ✓ | — | ✓ |
| Basic memory MCP | ✓ | Varies | Varies | Varies | Varies |
| Hosted agent memory | ✓ | Varies | ✓ | Provider-defined | — |
| Global Agent Memory | ✓ | ✓ | ✓ | ✓ | Markdown |
Use project instruction files for compact rules that always belong in a prompt. Use Global Agent Memory when knowledge should be searchable, shared between clients, reviewed by a person, updated over time, or hidden behind explicit permission.
sqlite-vec add semantic ranking.127.0.0.1 and requires a generated bearer token stored outside the Vault.The opt-in performance suite creates 10,000 synthetic memories and exercises the same indexing and retrieval paths used by both runtime modes. On the recorded macOS ARM64 baseline, a full rebuild takes 36.5 seconds, warm keyword search P95 is 56 ms, warm hybrid search P95 is 76 ms, and incremental stdio proxy overhead is 1.5 ms. Results vary by machine; the changed-note, search, and proxy budgets run as regression gates. See the methodology and complete baseline.
Global Agent Memory is more than an MCP server. Agents, owners, and knowledge workers use the same canonical memories through three purpose-built surfaces:
| Surface | Designed for | What it provides |
|---|---|---|
| MCP | Claude Code, Codex, and other agents | Project-aware context, search, candidate creation, safe updates, lifecycle actions, and permission requests through a frozen V1 contract |
| Obsidian Vault | Reading, writing, linking, and long-term knowledge ownership | Portable Markdown and YAML, templates, native Bases views, project overview hubs, wikilinks, backlinks, graph navigation, and direct-edit synchronization |
| Local dashboard | Fast owner review and administration | Candidate approval and editing, conflict comparison, visibility classification, protected-access decisions, search, projects, activity, backups, and system health |
The Vault is the durable source of truth. The dashboard is a complementary control plane, and the MCP interface is the safe automation layer used by agents. You can use Obsidian, the dashboard, or both without creating separate copies of your memory.
Real dashboard UI with synthetic Atlas project data. No private Vault content is shown.
This is the shortest path to persistent memory for Claude Code, Codex, and other MCP clients. The guided installer creates the local service, Obsidian-compatible Vault, dashboard, MCP registrations, and agent skills together.
uvuv tool install global-memory-mcp
To install the latest unreleased source, use uv tool install git+https://github.com/ozankasikci/global-agent-memory.git. For a local checkout, use uv tool install ..
global-memory setup
Setup shows one plan and asks once before it changes anything. It initializes the local Vault, creates the protected token, detects Claude Code and Codex, installs their MCP integrations and skills, verifies healthy clients, and opens the dashboard. Opening the dashboard starts its authenticated localhost server on demand. The command is idempotent, so running it again repairs or updates managed components without replacing unrelated client configuration.
Use flags when you need a non-default setup:
# Non-interactive installation
global-memory setup --yes
global-memory setup --vault "$HOME/Memory"
global-memory setup --clients claude-code global-memory setup --clients none
global-memory setup --service
global-memory setup --dry-run
Setup installs five basic shortcuts for each detected client:
| Shortcut | Purpose |
|---|---|
gam-context | Load project-aware context for a task |
gam-search | Find a decision, fact, error, convention, or solution |
gam-remember | Propose explicitly supplied durable knowledge as a candidate |
gam-review | Show the candidate queue without changing it |
gam-dashboard | Open the authenticated dashboard |
In Claude Code, invoke them directly, for example /gam-context fix the upload retry bug. In Codex, type /skills and choose one, or mention it directly, for example $gam-context fix the upload retry bug.
global-memory dashboard
You can also ask a connected agent:
Open the Global Agent Memory dashboard.
The agent calls memory_dashboard_open and opens the same authenticated local dashboard.
The individual commands remain available for advanced setups and troubleshooting:
global-memory init --vault "$HOME/Documents/Global Agent Memory"
global-memory daemon install-service --kind launchd # use systemd on Linux global-memory integrations install all global-memory integrations verify all global-memory doctor
After integration, you normally describe your intent instead of running memory commands manually.
Before you start, load the relevant memory for this project and summarize the
conventions and recent decisions.
Remember that production ARM64 binaries must be built locally and uploaded to the
server. Add it as a project convention with the deployment discussion as evidence.
The agent creates a candidate. Nothing becomes active until it is approved.
Find the deployment memory and update it with the new health-check command. Do not
create a duplicate.
Open the memory dashboard so I can review the candidates.
The shared integration skill teaches supported agents when to retrieve, propose, update, and avoid duplicating memory.
The configured Obsidian Vault is the human-readable, durable source of truth—not an export of an opaque database. Every managed memory is a normal Markdown file with YAML properties, a stable memory ID, lifecycle metadata, and project-aware links.
Initialization adds an Obsidian workspace without replacing your existing files:
Solo se muestra el principio; lee el resto en el repo