{
  "id": "knowledge-fabric-impl:supermemory.api",
  "_kind": "KnowledgeFabricImpl",
  "_file": "agent-stack/supermemory/supermemory-api.yaml",
  "_cluster": "agent-stack",
  "attributes": {
    "displayName": "Supermemory REST API & MCP Server",
    "agentVersionId": "agentVersion:supermemory:current",
    "fabricKind": "cloud-api-and-mcp",
    "description": "Cloud REST API (api.supermemory.ai) and MCP Server 4.0 for agent\nmemory operations. REST API provides document ingestion, memory\nmanagement, profile retrieval, and hybrid search. MCP server\n(mcp.supermemory.ai/mcp) exposes four tools: addMemory, search,\ngetProjects, whoAmI. Built on Cloudflare Workers with Durable\nObjects for persistent sessions. SDKs for TypeScript (npm\nsupermemory) and Python (pip supermemory).\n",
    "apiBaseUrl": "https://api.supermemory.ai",
    "mcpUrl": "https://mcp.supermemory.ai/mcp",
    "authentication": {
      "primary": "OAuth via /.well-known/oauth-protected-resource",
      "alternative": "Bearer token with sm_ prefix"
    },
    "keyEndpoints": [
      "POST /v3/documents -- ingest content (text, URL, PDF, image, video)",
      "GET /v3/profile -- retrieve user profile (static + dynamic)",
      "GET /v3/search -- semantic/hybrid search with metadata filtering",
      "POST /v3/memories -- create/update memories",
      "DELETE /v3/memories -- soft-delete (forget)"
    ],
    "mcpTools": [
      "addMemory -- save information with optional project scoping",
      "search -- retrieve memories and profiles",
      "getProjects -- list available projects",
      "whoAmI -- authenticated user details"
    ],
    "sdkUsage": "TypeScript: client.add(), client.profile(), client.search.memories()\nPython: client.add(), client.profile(), client.search()\nBoth support containerTag for user/project scoping.\n",
    "processingPipeline": "Queued -> Extracting -> Chunking -> Embedding -> Indexing -> Done",
    "knowledgeGraphRelationships": [
      "Update -- new info contradicts old, tracks isLatest",
      "Extend -- new info enriches without replacing",
      "Derive -- system infers connections from patterns"
    ],
    "ingestionOptions": {
      "taskType": "memory (full context layer) or superrag (managed RAG)",
      "dreaming": "dynamic (batch related docs) or instant (process immediately)",
      "containerTag": "scope to user/project (max 100 chars)",
      "metadata": "key-value pairs for filtering"
    },
    "ourEquivalent": "Our MCP client can consume Supermemory's MCP server directly by\nadding its endpoint to .mcp.json. However, for orchestrated agent\nruns, the SMFS approach (supermemory-smfs.yaml) is preferred over\nraw MCP tools because it avoids adding cognitive load to the agent\nprompt. The REST API is most useful for the orchestrator layer\n(genty-platform) to perform structured memory operations like\nprofile retrieval at run start or batch memory ingestion at run end.\n"
  },
  "outgoingEdges": [
    {
      "from": "knowledge-fabric-impl:supermemory.api",
      "to": "layer:12-knowledge-fabric",
      "kind": "realizes",
      "attributes": {}
    },
    {
      "from": "knowledge-fabric-impl:supermemory.api",
      "to": "agent:supermemory",
      "kind": "part_of",
      "attributes": {}
    },
    {
      "from": "knowledge-fabric-impl:supermemory.api",
      "to": "protocol:mcp",
      "kind": "integrates_with",
      "attributes": {}
    },
    {
      "from": "knowledge-fabric-impl:supermemory.api",
      "to": "tool:supermemory-sdk",
      "kind": "integrates_with",
      "attributes": {}
    }
  ],
  "incomingEdges": []
}