Content Interviewer MCP

Content Interviewer MCP is a local Python MCP server that discovers research topics, interviews you to uncover your unique perspective, and turns your insights into content such as short-form Reel scripts.

Project status

The MVP is complete and ready for local use with MCP-compatible clients such as Codex.

Related MCP server: mcp-usercall

Requirements

• Python 3.11 or newer

• SQLite with FTS5 support

Development setup

Create a virtual environment:

python3 -m venv .venv

Activate it:

source .venv/bin/activate

Install the project and its development dependencies:

python -m pip install -e ".[dev]"

Development checks

Run the tests:

python -m pytest

Run linting:

python -m ruff check .

Check that the source compiles:

python -m compileall -q src

Architecture

The initial version uses:

• the official Python MCP SDK

• Pydantic for input validation

• SQLite for local persistence

• SQLite FTS5 for full-text search

• pytest for automated testing

• Ruff for linting

• STDIO for communication with Codex

The project starts as a local, single-user application. SQLite keeps private data local without requiring a separate database server. FTS5 provides the initial search implementation; embeddings will only be considered after the MVP demonstrates a need for them.

Project structure

src/
  content_interviewer/
    server.py
    config.py
    db/
      connection.py
      migrations/
      repositories/
    services/
    tools/
    schemas/
    utils/
    resources/
tests/
fixtures/
docs/
data/

Privacy

ChatGPT exports, SQLite databases, environment files, logs, and other private local data must not be committed to version control. The server must not log complete imported conversations or article bodies.

MVP boundaries

Version 0.1 does not include a web dashboard, multi-user accounts, remote deployment, embeddings, automatic social-media publishing, or live access to a ChatGPT account.