PersonaMCP MCP server

PersonaMCP

Your communication style and memory for AI agents.

PersonaMCP imports your conversation exports, measures how you write, and gives an AI agent a compact style profile plus relevant incoming-message/reply examples. Your raw history stays on your computer. There is no model training, web dashboard, cloud embedding requirement, telemetry, or automatic reply generation.

Writing preferences are usually too vague: “sound casual” does not capture someone who uses lowercase, sends three short messages, switches languages, or writes differently to a colleague. PersonaMCP gives the connected writer evidence instead of a guessed personality.

Install

Python 3.11 or newer. Install from PyPI:

python -m pip install personamcp
persona --help

Or run it without installing, using uv: uvx personamcp --help.

To work from a checkout of this repository:

git clone https://github.com/robyroro/PersonaMCP.git
cd PersonaMCP
uv sync --locked
uv run persona --help

Or install into your own virtual environment:

python -m venv .venv
# Linux/macOS: source .venv/bin/activate
# Windows PowerShell: .venv\Scripts\Activate.ps1
python -m pip install .
persona --help

In a uv checkout, prefix the persona commands below with uv run. With an activated pip installation, run persona directly.

The base installation supports import, analysis, FTS search, lexical interaction retrieval, and MCP. Semantic retrieval is an optional, fully local extra:

After initialization and imports (described below):

uv sync --locked --extra semantic
uv run persona model prepare
uv run persona index

With pip, use python -m pip install '.[semantic]'. Preparing the model explicitly downloads weights from Hugging Face and pins their immutable revision. It does not read or send chats. Indexing and subsequent queries load only local files with remote code disabled.

Quick start

persona init
persona config set-name "Robert"
persona config add-alias "roby"
persona config set-name "Exact Instagram display name" --platform instagram
persona config set-name "snapchat_username" --platform snapchat

persona import instagram ./instagram-export/
persona import snapchat ./snapchat-export/
persona import whatsapp ./chat.txt
persona import json ./messages.json

persona stats
persona analyze
persona search "cat costa"
persona similar "mai vii azi?" --person "David"
persona writing-context "ce faci diseara?" --person "David" --platform instagram

For a synthetic first run, use a separate data directory:

persona --home ./sample-persona init
persona --home ./sample-persona config set-name "Owner"
persona --home ./sample-persona import json ./examples/messages.json
persona --home ./sample-persona analyze
persona --home ./sample-persona writing-context "mai vii azi la cafea?" --person "Alex"

Put private imports and custom data directories outside your repository. The included .gitignore covers conventional private folders but cannot protect every arbitrarily named path.

Identity must match an exact exported sender name or sender ID. Platform aliases override global names on that platform. No participant is guessed from message volume. An import matching no owner messages fails before writing anything. Changing names/aliases recomputes ownership and interactions and invalidates profiles/vectors; run analyze and index again.

Supported imports

Shortened. The full README is on GitHub.