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Persistent AI memory in one SQLite file: 3-layer hybrid search, confidence scoring, 29 tools.
CPersona is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 73/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding CPersona to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
uvx cpersona==2.5.3Review the upstream source before running this command.
{
"_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."
}
}