CortexPlus
Personal memory layer: files, notes, messages, tasks and email, semantically indexed.
Sollte ich dies verwenden
Qualität und Sicherheit
Befunde (1)
- LOWTool 'fetch' suggests web access but openWorldHint=falsein fetch
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"cortexplus": {
"url": "https://mcp.cortexplus.io/mcp"
}
}
}Remote-Endpunkte
https://mcp.cortexplus.io/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (11)
🟢search(query, limit)
Search the user's CortexPlus memory and return ranked matches. Use this to find what the user has stored before answering from memory.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "What to look for, in natural language."
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"default": 10
}
},
"required": [
"query"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"results": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
},
"url": {
"type": "string"
},
"text": {
"type": "string"
}
},
"required": [
"id",
"title",
"url"
]
}
}
},
"required": [
"results"
]
}🟢fetch(id)
Retrieve the full content of one CortexPlus memory item by id, as returned by search.
Eingabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Item id from a search result."
}
},
"required": [
"id"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
},
"text": {
"type": "string"
},
"url": {
"type": "string"
},
"metadata": {
"type": "object"
}
},
"required": [
"id",
"title",
"text",
"url"
]
}🟢recall(query, limit, depth, maxChars)
Build a context block from the user's CortexPlus memory: the passages that answer a question plus their graph neighbours, already formatted as text. Prefer this over search when you intend to answer from the user's memory.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"default": 10
},
"depth": {
"type": "integer",
"minimum": 0,
"maximum": 3,
"default": 1
},
"maxChars": {
"type": "integer",
"minimum": 500,
"maximum": 20000,
"default": 6000
}
},
"required": [
"query"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"text": {
"type": "string"
},
"matches": {
"type": "integer"
}
},
"required": [
"text",
"matches"
]
}⚪remember(title, content, tags, type, parentId)
Store a note in the user's CortexPlus memory so future conversations can recall it.
Eingabe-Schema
{
"type": "object",
"properties": {
"title": {
"type": "string"
},
"content": {
"type": "string"
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
},
"type": {
"type": "string",
"default": "note",
"description": "Node type, e.g. note or meeting-note."
},
"parentId": {
"type": "string",
"description": "Optional id of an existing memory to nest this one under."
}
},
"required": [
"content"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
}
},
"required": [
"id"
]
}🟡memory(text, tags)
Save a memory in CortexPlus. CortexPlus decides whether it is a note, task, or reminder and extracts the client.
Eingabe-Schema
{
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "Text to classify and save."
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
}
},
"required": [
"text"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"type": {
"type": "string"
},
"title": {
"type": "string"
},
"client": {
"type": [
"string",
"null"
]
},
"status": {
"type": [
"string",
"null"
]
},
"memory": {
"type": [
"string",
"null"
]
},
"review": {
"type": [
"string",
"null"
]
},
"resolved": {
"type": [
"boolean",
"null"
]
},
"url": {
"type": "string"
}
},
"required": [
"id",
"type",
"title",
"client",
"status",
"memory",
"review",
"resolved",
"url"
]
}🟢tasks(status, client, limit)
List open CortexPlus tasks and reminders, optionally filtered by client.
Eingabe-Schema
{
"type": "object",
"properties": {
"status": {
"type": "string",
"default": "open"
},
"client": {
"type": "string"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"default": 20
}
},
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"tasks": {
"type": "array",
"items": {
"type": "object",
"required": [
"id",
"title",
"client",
"status",
"dueAt",
"url"
],
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
},
"client": {
"type": [
"string",
"null"
]
},
"status": {
"type": [
"string",
"null"
]
},
"dueAt": {
"type": [
"string",
"null"
]
},
"url": {
"type": "string"
}
}
}
}
},
"required": [
"tasks"
]
}🟡save_context(content, platform, key, title, model, ...)
Save a handoff summary of this conversation to the user's CortexPlus memory so it can be resumed later in another AI platform. Write the summary yourself, in Markdown, covering: objective, decisions taken, current state, artifacts, next steps and constraints. Do not paste the raw transcript. Never include passwords, API keys or tokens.
Eingabe-Schema
{
"type": "object",
"properties": {
"content": {
"type": "string",
"description": "Handoff summary in Markdown."
},
"platform": {
"type": "string",
"description": "The AI platform you are running on, e.g. ChatGPT, Claude, Gemini, Cursor."
},
"key": {
"type": "string",
"description": "Short stable slug for the topic, e.g. context-pack-design. Sending the same key again updates the pack instead of creating another."
},
"title": {
"type": "string"
},
"model": {
"type": "string"
},
"messageCount": {
"type": "integer",
"minimum": 0,
"maximum": 100000
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
}
},
"required": [
"content",
"platform",
"key"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
},
"url": {
"type": "string"
},
"created": {
"type": "boolean"
},
"redactions": {
"type": "array",
"items": {
"type": "object",
"required": [
"kind",
"placeholder",
"count"
],
"properties": {
"kind": {
"type": "string"
},
"placeholder": {
"type": "string"
},
"count": {
"type": "integer"
}
}
}
}
},
"required": [
"id",
"title",
"url",
"created",
"redactions"
]
}🟢resume(query, id, maxChars)
Load a previously saved CortexPlus context pack to resume work started in another AI conversation.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Topic to find the pack by, in natural language."
},
"id": {
"type": "string",
"description": "Pack id, as returned by context_packs."
},
"maxChars": {
"type": "integer",
"minimum": 500,
"maximum": 20000,
"default": 6000
}
},
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"text": {
"type": "string"
},
"pack": {
"type": [
"object",
"null"
],
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
},
"url": {
"type": "string"
}
}
},
"matches": {
"type": "integer"
}
},
"required": [
"text",
"pack",
"matches"
]
}🟢context_packs(platform, limit)
List saved CortexPlus context packs, optionally filtered by AI platform.
Eingabe-Schema
{
"type": "object",
"properties": {
"platform": {
"type": "string",
"description": "Platform filter, e.g. chatgpt or claude."
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"default": 20
}
},
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"packs": {
"type": "array",
"items": {
"type": "object",
"required": [
"id",
"title",
"platform",
"url",
"savedAt"
],
"properties": {
"id": {
"type": "string"
},
"title": {
"type": "string"
},
"platform": {
"type": [
"string",
"null"
]
},
"url": {
"type": "string"
},
"savedAt": {
"type": [
"string",
"null"
]
}
}
}
}
},
"required": [
"packs"
]
}🟡signup(email, name, client)
Create a CortexPlus account, or begin signing in to an existing one, so this conversation can use CortexPlus as the user's long-term memory and knowledge base. Ask the user for their email address, and for their name if you do not already have it, then call this tool. CortexPlus sends them a short authentication key by email; ask the user for that key and call connect with it. Never guess or invent the email address.
Eingabe-Schema
{
"type": "object",
"properties": {
"email": {
"type": "string",
"description": "The user's email address. Ask the user; never guess or invent it."
},
"name": {
"type": "string",
"description": "The user's name, if it is not already known."
},
"client": {
"type": "string",
"description": "The name of the AI platform you are running on, e.g. ChatGPT, Claude, Cursor."
}
},
"required": [
"email"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"sent": {
"type": "boolean"
}
},
"required": [
"sent"
]
}🟡connect(key, client)
Complete the CortexPlus connection with the short authentication key the user received by email after signup. Ask the user to paste the key, then call this tool; never guess or invent the key. The response includes an API key that the AI platform should save in its CortexPlus connector configuration.
Eingabe-Schema
{
"type": "object",
"properties": {
"key": {
"type": "string",
"description": "The authentication key pasted by the user from their CortexPlus email."
},
"client": {
"type": "string",
"description": "The name of the AI platform you are running on, e.g. ChatGPT, Claude, Cursor."
}
},
"required": [
"key"
],
"additionalProperties": false
}Ausgabe-Schema
{
"type": "object",
"properties": {
"apiKey": {
"type": "string"
},
"email": {
"type": "string"
},
"name": {
"type": "string"
}
},
"required": [
"apiKey",
"email",
"name"
]
}Community
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