memra
Persistent memory for AI agents. EU-hosted, privacy-first, hybrid recall, contradiction detection.
Sollte ich dies verwenden
Qualität und Sicherheit
A
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
~2,653Tokens (Tool-Definitionen)
~4.2 KBTypische Antwortgröße
Erhebliche Auswirkung auf die Aufmerksamkeit (2.07% von 128k Kontext)
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": {
"memra": {
"url": "https://usememra.com/mcp"
}
}
}Remote-Endpunkte
https://usememra.com/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (7)
🟢 Nur lesen🟡 Schreiben🔴 Löschen⚪ Unbekannt
⚪memra_remember(content, namespace, type, importance, tags, ...)
Store one or many memories in Memra. Single mode: pass content + namespace. Decision mode: pass type=decision with content + namespace (optionally context). Pattern mode: pass type=pattern with title + steps + namespace. Bulk mode: pass entries[]. If the response contains conflicts[], the new fact contradicts those existing memories — review them and use memra_supersede on the outdated one instead of leaving both active.
Eingabe-Schema
{
"type": "object",
"properties": {
"content": {
"type": "string",
"maxLength": 10000,
"description": "Single/decision mode: memory content. Required unless using entries[] or pattern mode."
},
"namespace": {
"type": "string",
"description": "Tenant namespace. Required for single, decision, and pattern modes."
},
"type": {
"type": "string",
"enum": [
"fact",
"event",
"pattern",
"working",
"decision",
"preference",
"context",
"entity",
"reference"
],
"default": "fact",
"description": "Memory type; use decision for decision mode and pattern for pattern mode."
},
"importance": {
"type": "integer",
"minimum": 1,
"maximum": 10,
"default": 5
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
},
"metadata": {
"type": "object"
},
"mask": {
"type": "boolean",
"default": false
},
"project_id": {
"type": "string",
"description": "Project ID (required if account has multiple projects)"
},
"entries": {
"type": "array",
"items": {
"type": "object"
},
"description": "Bulk mode: array of memory entries (max 25). When provided, the server routes to batch create."
},
"context": {
"type": "string",
"description": "Decision mode: reasoning/context for the decision."
},
"steps": {
"type": "array",
"items": {
"type": "string"
},
"description": "Pattern mode: ordered steps. Required with title when type=pattern."
},
"gotchas": {
"type": "array",
"items": {
"type": "string"
},
"description": "Pattern mode: common pitfalls."
},
"verify_checklist": {
"type": "array",
"items": {
"type": "string"
},
"description": "Pattern mode: verification checklist."
},
"title": {
"type": "string",
"description": "Pattern mode: title. Required with steps when type=pattern."
}
}
}Ausgabe-Schema
{
"type": "object",
"oneOf": [
{
"type": "object",
"properties": {
"memory_id": {
"type": "string"
},
"action": {
"type": "string",
"enum": [
"created",
"duplicate_found"
]
},
"type": {
"type": "string"
},
"namespace": {
"type": "string"
},
"project_id": {
"type": "string"
},
"revision": {
"type": "integer",
"description": "Read-your-writes token — pass to memra_recall as wait_for_revision to guarantee this write is searchable."
},
"embedding_status": {
"type": "string",
"enum": [
"pending",
"complete",
"failed"
]
},
"conflicts": {
"type": "array",
"description": "Existing memories this new fact contradicts (NLI-scored). Review each and memra_supersede the outdated one.",
"items": {
"type": "object",
"properties": {
"memory_id": {
"type": "string"
},
"preview": {
"type": "string"
},
"confidence": {
"type": "number"
}
},
"required": [
"memory_id",
"preview",
"confidence"
]
}
}
},
"required": [
"memory_id",
"action"
]
},
{
"type": "object",
"properties": {
"total": {
"type": "integer"
},
"created": {
"type": "integer"
},
"results": {
"type": "array",
"items": {
"type": "object"
}
}
},
"required": [
"total",
"created",
"results"
]
}
]
}🟢memra_recall(query, namespace, type, min_confidence, limit, ...)
Search memories in Memra by semantic similarity. Returns ranked results by relevance. Replaces memra_search.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query for semantic matching"
},
"namespace": {
"type": "string",
"description": "Tenant namespace to search within"
},
"type": {
"type": "string",
"enum": [
"fact",
"event",
"pattern",
"working",
"decision",
"preference",
"context",
"entity",
"reference"
],
"description": "Filter by memory type"
},
"min_confidence": {
"type": "number",
"minimum": 0,
"maximum": 1,
"description": "Minimum confidence score"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 50,
"default": 10,
"description": "Max results to return"
},
"project_id": {
"type": "string",
"description": "Filter by project ID"
},
"tags": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by tags"
},
"wait_for_revision": {
"type": "integer",
"minimum": 0,
"description": "Read-your-writes: pass the revision returned by memra_remember to block (max 5s) until that write is indexed and searchable. Use when recalling something you just stored."
},
"max_tokens": {
"type": "integer",
"minimum": 100,
"description": "Token budget: return the best-scoring results that fit within this many tokens (chars/4 heuristic). Combine with a higher limit to fill the budget."
},
"not_tags": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude memories carrying any of these tags."
},
"since": {
"type": "string",
"description": "Only memories created at or after this ISO-8601 date."
},
"until": {
"type": "string",
"description": "Only memories created at or before this ISO-8601 date."
},
"used_ids": {
"type": "array",
"items": {
"type": "string"
},
"description": "Feedback: memory IDs from your PREVIOUS recall that you actually used. They gain a small permanent ranking boost — pass these every time to make recall learn."
}
},
"required": [
"query",
"namespace"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"results": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"memory_id": {
"type": "string"
},
"uri": {
"type": "string"
},
"excerpt": {
"type": "string"
},
"content": {
"type": "string"
},
"score": {
"type": "number"
},
"type": {
"type": [
"string",
"null"
]
},
"importance": {
"type": [
"integer",
"null"
]
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
},
"created_at": {
"type": [
"string",
"null"
]
},
"content_origin": {
"type": [
"string",
"null"
]
},
"trust_state": {
"type": "string"
},
"full_content_available": {
"type": "boolean"
},
"untrusted_content": {
"type": "boolean"
},
"content_classification": {
"type": "string"
},
"staleness_score": {
"type": [
"integer",
"null"
],
"description": "0 (fresh) to 100 (critical). High values mean the memory may be outdated — verify before relying on it."
},
"staleness_status": {
"type": [
"string",
"null"
],
"enum": [
"fresh",
"aging",
"stale",
"critical",
null
]
},
"last_confirmed": {
"type": [
"string",
"null"
],
"description": "When this memory was last written or refreshed."
}
},
"required": [
"id",
"uri",
"excerpt",
"score",
"trust_state",
"untrusted_content"
]
}
},
"total_candidates": {
"type": "integer"
},
"estimated_tokens": {
"type": "integer"
}
},
"required": [
"results",
"total_candidates"
]
}🟢memra_get(memory_id)
Get a single memory by ID with full content. Use when you need the complete text of a memory (search results are truncated).
Eingabe-Schema
{
"type": "object",
"properties": {
"memory_id": {
"type": "string",
"description": "The memory ID to retrieve"
}
},
"required": [
"memory_id"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
},
"uri": {
"type": "string"
},
"type": {
"type": "string"
},
"importance": {
"type": [
"integer",
"null"
]
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
},
"content": {
"type": "string"
},
"metadata": {
"type": [
"object",
"array",
"null"
]
},
"project_id": {
"type": [
"string",
"null"
]
},
"namespace": {
"type": [
"string",
"null"
]
},
"content_origin": {
"type": [
"string",
"null"
]
},
"trust_state": {
"type": "string"
},
"verified_by": {
"type": [
"string",
"null"
]
},
"verification_method": {
"type": [
"string",
"null"
]
},
"untrusted_content": {
"type": "boolean"
},
"content_classification": {
"type": "string"
},
"created_at": {
"type": [
"string",
"null"
]
},
"updated_at": {
"type": [
"string",
"null"
]
}
},
"required": [
"id",
"uri",
"type",
"content",
"trust_state",
"untrusted_content"
]
}🟢memra_list(namespace, type, tags, limit, offset, ...)
List memories in Memra for a namespace. Returns paginated results with filtering options.
Eingabe-Schema
{
"type": "object",
"properties": {
"namespace": {
"type": "string",
"description": "Tenant namespace"
},
"type": {
"type": "string",
"enum": [
"fact",
"event",
"pattern",
"working",
"decision",
"preference",
"context",
"entity",
"reference"
],
"description": "Filter by memory type"
},
"tags": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by tags"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 100,
"default": 20,
"description": "Max results"
},
"offset": {
"type": "integer",
"default": 0,
"description": "Pagination offset"
},
"project_id": {
"type": "string",
"description": "Filter by project ID"
},
"min_importance": {
"type": "integer",
"minimum": 1,
"maximum": 10,
"description": "Minimum importance"
}
},
"required": [
"namespace"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"memories": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"type": {
"type": "string"
},
"importance": {
"type": "integer"
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
},
"created_at": {
"type": "string"
}
},
"required": [
"id",
"type"
]
}
},
"total": {
"type": "integer"
}
},
"required": [
"memories",
"total"
]
}🟡memra_supersede(memory_id, content, importance, tags, metadata)
Replace a memory with new content. The old memory is marked superseded and stops appearing in search; the new memory inherits the old memory's type, importance, tags, source and metadata unless overridden. Works for all memory types (use this instead of memra_add when you are correcting or updating existing knowledge).
Eingabe-Schema
{
"type": "object",
"properties": {
"memory_id": {
"type": "string",
"description": "ID of the memory to supersede"
},
"content": {
"type": "string",
"maxLength": 10000,
"description": "New content that replaces the old memory"
},
"importance": {
"type": "integer",
"minimum": 1,
"maximum": 10,
"description": "Override importance (defaults to old memory's importance)"
},
"tags": {
"type": "array",
"items": {
"type": "string"
},
"description": "Override tags (defaults to old memory's tags)"
},
"metadata": {
"type": "object",
"description": "Override metadata (defaults to old memory's metadata)"
}
},
"required": [
"memory_id",
"content"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"new_memory_id": {
"type": "string"
},
"superseded_memory_id": {
"type": "string"
},
"type": {
"type": "string"
},
"revision": {
"type": "integer",
"description": "Read-your-writes token — pass to memra_recall as wait_for_revision."
},
"embedding_status": {
"type": "string",
"enum": [
"pending",
"complete",
"failed"
]
}
},
"required": [
"new_memory_id",
"superseded_memory_id",
"type"
]
}🟡memra_history(memory_id)
View the full supersession chain for a memory (oldest to newest). Use this when you need to audit how a fact or decision evolved over time — e.g., the user asks "why did we change X?", you need to understand prior reasoning before proposing another change, or you spotted a superseded_by reference and need the full timeline. Given any memory ID in the chain, returns every predecessor and successor.
Eingabe-Schema
{
"type": "object",
"properties": {
"memory_id": {
"type": "string",
"description": "Any memory ID in the chain"
}
},
"required": [
"memory_id"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"chain": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"type": {
"type": "string"
},
"status": {
"type": "string"
},
"superseded_by": {
"type": [
"string",
"null"
]
},
"created_at": {
"type": "string"
}
},
"required": [
"id",
"type",
"status"
]
}
},
"length": {
"type": "integer"
}
},
"required": [
"chain",
"length"
]
}⚪memra_bootstrap(namespace, agent_id, max_tokens, include_types, exclude_types, ...)
Load agent bootstrap context from Memra. Returns priority-ordered memories for agent session initialization.
Eingabe-Schema
{
"type": "object",
"properties": {
"namespace": {
"type": "string",
"description": "Tenant namespace"
},
"agent_id": {
"type": "string",
"description": "Agent identifier, defaults to API key ID"
},
"max_tokens": {
"type": "integer",
"default": 500,
"description": "Token budget for bootstrap payload"
},
"include_types": {
"type": "array",
"items": {
"type": "string"
},
"description": "Only include these memory types"
},
"exclude_types": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude these memory types"
},
"recency_days": {
"type": "integer",
"default": 7,
"description": "Include context from last N days"
},
"project_id": {
"type": "string",
"description": "Project ID (required if account has multiple projects)"
}
},
"required": [
"namespace"
]
}Ausgabe-Schema
{
"type": "object",
"properties": {
"memories": {
"type": "array",
"items": {
"type": "object",
"properties": {
"uri": {
"type": "string"
},
"content_origin": {
"type": [
"string",
"null"
]
},
"untrusted_content": {
"type": "boolean"
},
"content_classification": {
"type": "string"
},
"trust_state": {
"type": "string"
}
},
"required": [
"uri",
"untrusted_content",
"content_classification"
]
}
},
"token_estimate": {
"type": "integer"
},
"health_warnings": {
"type": "array",
"items": {
"type": "object"
}
},
"revision": {
"type": "integer"
}
},
"required": [
"memories",
"token_estimate"
]
}Community
Nachweis
Aktuelle Beobachtungen
verifiziertVersion nicht aufgezeichnet7 Tools
verifiziertVersion nicht aufgezeichnet7 Tools