CPersona

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-07-30T06:05:10.693707Z",
      "publishedAt": "2026-07-30T06:05:10.693707Z",
      "statusChangedAt": "2026-07-30T06:05:10.693707Z"
    }
  },
  "server": {
    "name": "io.github.Cloto-dev/cpersona",
    "title": "CPersona",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "2.5.3",
    "packages": [
      {
        "version": "2.5.3",
        "transport": {
          "type": "stdio"
        },
        "identifier": "cpersona",
        "runtimeHint": "uvx",
        "registryType": "pypi",
        "registryBaseUrl": "https://pypi.org",
        "environmentVariables": [
          {
            "name": "CPERSONA_DB_PATH",
            "default": "data/cpersona.db",
            "description": "SQLite database path. Defaults to data/cpersona.db, which follows the client's working directory — set it to an absolute path to keep one memory across sessions."
          },
          {
            "name": "CPERSONA_EMBEDDING_MODE",
            "default": "none",
            "description": "Embedding mode: 'http' to use an embedding server for vector search, 'none' for lexical layers only."
          },
          {
            "name": "CPERSONA_EMBEDDING_URL",
            "description": "Embedding server endpoint, e.g. http://127.0.0.1:8401/embed. Required when CPERSONA_EMBEDDING_MODE=http."
          },
          {
            "name": "CPERSONA_RECALL_MODE",
            "default": "rrf",
            "description": "Recall fusion strategy: 'rrf' (default), 'rsf', or 'cascade'."
          }
        ]
      }
    ],
    "repository": {
      "url": "https://github.com/Cloto-dev/cpersona",
      "source": "github"
    },
    "websiteUrl": "https://github.com/Cloto-dev/cpersona#readme",
    "description": "Persistent AI memory in one SQLite file: 3-layer hybrid search, confidence scoring, 29 tools."
  }
}