Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Self-learning memory for AI agents, powered by the Ragionex context engine.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
RAGIONEX_MEMORY_API_KEYAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@ragionex/memory-mcp"
],
"env": {
"RAGIONEX_MEMORY_API_KEY": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add memory --env RAGIONEX_MEMORY_API_KEY=your-value -- npx -y @ragionex/memory-mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@ragionex/memory-mcp"
],
"env": {
"RAGIONEX_MEMORY_API_KEY": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"memory": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@ragionex/memory-mcp"
],
"env": {
"RAGIONEX_MEMORY_API_KEY": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto ragionex bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: RAGIONEX_MEMORY_API_KEY
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.8.0) kam gestern in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Ragionex Memory
Context engine and self-learning memory for AI agents
Your agents save what matters on their own, fix what changed and pick up where you left off in every new session.
Keep each project in its own Vault, give every key only the access it needs, and share memory with your team.
Set Up in One Line · Quick Start · Documentation · Pricing
Paste this into your agent:
Set up Ragionex Memory for yourself by following the instructions at https://ragionex.com/setup.
If you are an AI agent: follow the instructions at https://ragionex.com/setup.
In a terminal, on Windows (PowerShell or Command Prompt):
npx.cmd -y @ragionex/memory-mcp@latest install
On macOS or Linux:
npx -y @ragionex/memory-mcp@latest install
If your agent is not listed and has a global instructions file, choose manual setup. Run the setup once for each agent you use.
Ask your agent:
Check my Ragionex Memory connection.
It answers with your Vaults and what this agent may do in each.
Claude Desktop, Cursor, Cline and other clients that run local MCP servers use the same tools. Create a key at app.ragionex.com/keys and add the server to the client's user-global MCP config. On Windows:
{
"mcpServers": { "ragionex-memory-mcp": { "command": "cmd", "args": ["/c", "npx", "-y", "@ragionex/memory-mcp@latest"], "env": { "RAGIONEX_MEMORY_API_KEY": "rgx_memory_..." } } } }
On macOS or Linux:
{
"mcpServers": { "ragionex-memory-mcp": { "command": "npx", "args": ["-y", "@ragionex/memory-mcp@latest"], "env": { "RAGIONEX_MEMORY_API_KEY": "rgx_memory_..." } } } }
These clients get the tools but not the memory rule, so they use memory less consistently on their own. A client with a global instructions file can get the rule through manual setup instead. On Windows:
npx.cmd -y @ragionex/memory-mcp@latest install --manual
On macOS or Linux:
npx -y @ragionex/memory-mcp@latest install --manual
See the MCP Client Notes for client-specific details.
A Context Engine That Understands the Question. Your agent asks in plain language, and the engine understands what it means, even when it asks in different words than the memory was saved in. Even among thousands of memories, the right ones come first and arrive in milliseconds, so the agent reads only as much as it needs and its context stays lean. Memories come back exactly as they were saved: Ragionex never rewrites a memory or generates an answer.
Automatic Memory. Your agent saves what's worth keeping on its own: a document, a design decision, a preference, a project fact, something that was tried and how it turned out. It checks its memory before it answers, starts a task or asks you anything about your work, and the memory gets richer and more accurate the more you work. You can still tell it to remember or forget anything, any time.
Always Up to Date. A changed decision updates its record instead of adding a second one, and a record that turns out wrong is removed. Every change ends with one short line in the reply, so "undo that" is one sentence away. Every update carries the version its agent last read, so no agent can silently overwrite another's newer change.
Version History. Earlier versions of every memory, and deleted records in the trash, are kept for 30 days. Bring any of them back just by asking your agent, or from the dashboard.
Everything Visible in the Dashboard. Browse every memory your agents saved and see each one's status, who created or last edited it, and through which key. Open earlier versions, edit, restore or delete anything yourself, and export it all whenever you want.
Projects and Teams. Each project can keep its own memory in its own Vault, and a search never crosses into another. Every key carries its own Read, Create, Update and Delete permissions. Share a Vault with teammates, give each member their own permissions, and every member's agents draw from and add to the same memory.
Safe and Private. Memory text stored by Ragionex is kept in the EU and encrypted with AES-256. It is never sent to an outside AI service and never used to train AI models. Queued saves retry automatically.
Works Where You Work. One line sets up almost any AI agent on Windows, macOS and Linux. Other MCP clients connect too.
A Vault is a separate set of memories. A key decides what an agent may do in it. A member is a teammate the Vault's owner shared it with. The picture above shows them working together:
| Who | Read | Create | Update | Delete |
|---|---|---|---|---|
| Your agent 1 | ✅ | ✅ | ✅ | ✅ |
| Your agent 2 | ✅ | ✅ | ||
| Your agent 3 | ✅ | ✅ | ✅ | ✅ |
| Teammate A | ✅ | ✅ | ✅ | |
| Teammate B | ✅ |
The picture shows Create and Update as Write and Edit.
A new account starts with My vault as its default, and every project without its own Vault uses the default. To give a project its own memory, create a Vault in the Dashboard, then ask your agent to *use my acme-app Vault for this project*, or put a RAGIONEX_MEMORY.jsonc file in the project folder:
{
// The Vault this project uses (shown by the connection check and in the dashboard) "vault_id": " ", // Optional: a key only this project uses, for example one that can only read "api_key": "rgx_memory_..." }
.gitignore before putting a key in it.| Requests | Memory Size | Stored Memories | Vaults | Keys | Teammates |
|---|---|---|---|---|---|
| 10,000 per 30 days | 10,000 characters | Unlimited | 2 | 100 | 1 per Vault |
Saving, editing and restoring a memory each cost 1 request, and so does each search page fetched from the service. Browsing, viewing, deleting, the trash, version history, status checks and export are free. Free is for personal projects and evaluation and is in early access, so its limits may change. Commercial use is not permitted on Free; Pro is coming soon.
Tools
| Tool | Permission | Description |
|---|---|---|
ragionex_recall_memory | Read | Finds memories by meaning, one complete question at a time, with optional exact dates. Whole records arrive on numbered pages |
ragionex_list_memories | Read | Browses newest first with short previews, up to 100 per page |
ragionex_view_memory | Read | Returns the full text and revision of up to 50 records by ID |
ragionex_save_memory | Create | Saves a new record |
ragionex_update_memory | Update | Replaces a record's content, checked against the revision the agent last read |
ragionex_delete_memory | Delete | Moves records to the trash |
ragionex_list_trash | Read | Lists deleted records with their restore deadlines |
ragionex_memory_versions | Read | Lists retained versions or reads one in full |
ragionex_restore_memory | Update | Restores a trashed record or an older version as the next revision |
ragionex_memory_status | Read | Shows whether a new or edited record is still processing |
ragionex_memory_connection | Any valid key | Shows the selected Vault and why, every Vault the key can use, its permissions and any saves waiting on this machine |
Every record has id, vault_id, content, created_at, updated_at, status, revision, created_by and updated_by. New, edited and restored records must finish processing before recall can find them. Permanent deletion, export, Vault sharing, key management and account deletion live in the Dashboard.
Configuration, Updating and Uninstalling
| Setting | Details |
|---|---|
RAGIONEX_MEMORY_API_KEY | The agent's key. install creates it after you approve the connection in your browser and stores it in the agent's MCP registration |
RAGIONEX_MEMORY_INSTRUCTIONS_FILE | Manual setup only. The full path of the agent's global instructions file; the setup fills it in, and the memory rule in that file refreshes itself |
RAGIONEX_API_BASE | Optional API address, default https://api.ragionex.com |
| Relocated Agent Homes | install and uninstall follow CLAUDE_CONFIG_DIR, CODEX_HOME and XDG_CONFIG_HOME |
| Tool Timeout | Allow each MCP tool call more than 120 seconds, the connector's own request deadline, so a slow request still ends with its result or clear guidance |
| Windows | In WSL, run the setup inside the Linux environment where the agent runs |
| Diagnostics | The server writes to stderr; see your client's MCP server log |
Nur der Anfang wird gezeigt; den Rest findest du im Repo