Scribe MCP Server

Scribe MCP Server

Enables maintaining consistent project documentation and progress logs across development workflows. Provides tools for logging changes, tracking project phases, and keeping architecture docs synchronized with day-to-day development work.

Category
Visit Server

README

Scribe MCP Server

Scribe is a Model Context Protocol (MCP) server that keeps project documentation and progress logs consistent across agents. This repo ships a lightweight stdio server, filesystem/DB storage backends, and tooling to keep docs in sync with day-to-day development.

Prerequisites

  • Python 3.11+
  • pip (or your preferred package manager)
  • (Optional) PostgreSQL if you want shared storage instead of the default SQLite backend

Install Python dependencies:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Quick Start

  1. Install dependencies (see above).
  2. Choose a storage backend via environment variables:
    • SQLite (default): no action required.
    • PostgreSQL: set SCRIBE_STORAGE_BACKEND=postgres and SCRIBE_DB_URL=postgresql://....
  3. Launch the server:
    python server.py
    

Claude / MCP Configuration

Copy config/mcp_config.json into your Claude Desktop/Code MCP configuration and adjust the SCRIBE_ROOT path to point to this repository:

{
  "mcpServers": {
    "scribe": {
      "command": "python",
        "args": ["/absolute/path/to/scribe_mcp/server.py"],
        "env": {
        "SCRIBE_ROOT": "/absolute/path/to/scribe_mcp",
        "SCRIBE_STORAGE_BACKEND": "sqlite"
        }
    }
  }
}

Smoke Test

Verify the MCP server responds before wiring it into an IDE:

python scripts/test_mcp_server.py

This script runs a short-lived stdio session and checks that the server advertises tools.

Reminder Metadata

Every MCP tool responds with a reminders array containing context like stale docs, overdue logs, and the active project. Use these cues to keep architecture, phase plan, and checklist in lockstep with the work you’re doing.

Customising reminders

  • Set defaults.reminder inside a project config (or SCRIBE_REMINDER_DEFAULTS env JSON) to tweak behaviour. Example:
{
  "name": "scribe_mcp",
  "defaults": {
    "reminder": {
      "tone": "friendly",
      "log_warning_minutes": 15,
      "log_urgent_minutes": 30,
      "severity_weights": {"warning": 7, "urgent": 10}
    }
  }
}
  • Environment variables:
    • SCRIBE_REMINDER_IDLE_MINUTES — gap (minutes) before a new work session resets and warm-up kicks in (default: 45).
    • SCRIBE_REMINDER_WARMUP_MINUTES — grace period after resuming before warnings escalate (default: 5).
    • SCRIBE_REMINDER_DEFAULTS — JSON blob applied to every project when specific overrides aren’t set.

Project Structure

  • MCP_SPINE/ – container package for MCP servers.
    • scribe_mcp/ – Scribe server entrypoint, tools, storage backends, utilities.
    • config/projects/ – per-project Scribe configs.
    • config/mcp_config.json – sample MCP configuration for Claude.
    • docs/dev_plans/ – architecture, phase plan, checklist, and progress log.
    • scripts/test_mcp_server.py – smoke test for the MCP server.
    • tests/ – unit tests (run with pytest MCP_SPINE/tests).

Development Workflow

  1. Select a project with set_project (either via MCP tool or scripts/scribe.py).
  2. Use append_entry to log every meaningful change—Scribe tracks both the markdown log and (optionally) a database mirror.
  3. Keep docs aligned with implementation; reminder tooling surfaces when architecture/phase plan/checklist drift.

Troubleshooting

  • Missing MCP SDK: install pip install mcp if the server exits with “MCP Python SDK not installed.”
  • No tools returned: ensure scribe_mcp/tools/__init__.py imports all modules and that your virtual environment is active.
  • SQLite permissions: confirm SCRIBE_ROOT is writable; the server stores SQLite databases under the repo by default.

Contributing

  1. Run pytest MCP_SPINE/tests.
  2. Execute python MCP_SPINE/scripts/test_mcp_server.py.
  3. Update docs (MCP_SPINE/docs/dev_plans/scribe_mcp/…) and log your changes with MCP_SPINE/scripts/scribe.py.

Alright, here’s the no‑BS rundown for wiring your custom Scribe MCP server into Codex CLI on WSL. Follow the steps; swear at me later if it still doesn’t work.

1. Set up Scribe in your WSL project

  1. Clone / extract the repo and install dependencies. From ~/projects/Scribe, create a venv and install Python deps:

    cd ~/projects/Scribe
    python -m venv .venv
    source .venv/bin/activate
    pip install -r requirements.txt
    

    Scribe needs Python 3.11+; you already knew that.

  2. Decide on a storage backend.

    • SQLite (default): do nothing – Scribe will drop a .sqlite file in your project directory.
    • PostgreSQL: set SCRIBE_STORAGE_BACKEND=postgres and SCRIBE_DB_URL=postgresql://user:pass@host/db before launching the server.
  3. Pick a root for your docs/logs. Scribe uses SCRIBE_ROOT to find your project configs, dev plans and logs. Point this at the MCP_SPINE directory of your Scribe repo (e.g. /home/austin/projects/MCP_SPINE/scribe_mcp). This is where the per‑project configs live under config/projects/ – you can drop new YAML/JSON files there for each subproject.

2. Smoke‑test the server locally

Before hooking it to Codex, make sure the damn thing responds.

export SCRIBE_ROOT=/home/austin/projects/MCP_SPINE/scribe_mcp
export SCRIBE_STORAGE_BACKEND=sqlite   # or postgres with DB_URL
python -m MCP_SPINE.scribe_mcp.server

In another terminal you can run the provided smoke test:

python MCP_SPINE/scripts/test_mcp_server.py

The test fires up a short STDIO session, calls tools/list and checks that the server advertises tools. Fix any errors here before blaming Codex.

3. Tell Codex about your server

Codex CLI supports connecting to custom MCP servers via codex mcp add <name> ... or by editing the ~/.codex/config.toml file. The official docs confirm both methods.

Option A – use the CLI

Run this once to register Scribe as an MCP server (adjust paths/envs accordingly):

codex mcp add scribe \
  --env SCRIBE_ROOT=/home/austin/projects/MCP_SPINE/scribe_mcp \
  --env SCRIBE_STORAGE_BACKEND=sqlite \
  -- python -m MCP_SPINE.scribe_mcp.server
  • The --env flags set environment variables for the server. You can repeat --env for SCRIBE_DB_URL if using Postgres.
  • Everything after -- is the actual command used to launch the STDIO server.
  • Codex stores this in ~/.codex/config.toml for you.

You can verify it worked with codex mcp ls or by launching codex, entering its TUI, and typing /mcp. Healthy servers will show up there.

Option B – edit the config file

If you prefer hand‑editing, open ~/.codex/config.toml and append the following:

[mcp_servers.scribe]
command = "python"
args = ["-m", "MCP_SPINE.scribe_mcp.server"]

[mcp_servers.scribe.env]
SCRIBE_ROOT = "/home/austin/projects/MCP_SPINE/scribe_mcp"
SCRIBE_STORAGE_BACKEND = "sqlite"
# SCRIBE_DB_URL = "postgresql://…"  # uncomment for postgres

Codex reads this file on startup; the docs note that each MCP server lives under its own [mcp_servers.<name>] table with command, args and env entries. Save it and relaunch codex.

4. Kick the tires

  1. Launch Codex:

    codex
    
  2. Once inside the TUI, list MCP servers with /mcp. You should see scribe listed as healthy.

  3. Ask Codex to call a tool, e.g. /mcp call scribe tools/list to see what Scribe advertises. If that works, you’re good.

5. Dealing with multiple projects

  • Each project/subproject should have its own config file under MCP_SPINE/config/projects/. Name the file after the project (e.g. myapp.json or myapp.yaml) and define settings like defaults.reminder there.
  • Use Scribe’s set_project tool to switch between them at runtime; the server uses SCRIBE_ROOT to locate these configs.
  • Scribe logs docs/changes under docs/dev_plans/ per project, so keep your directory structure tidy.

6. Run it under Windows

Codex CLI’s Windows support is experimental; OpenAI recommends WSL—you’re already using it. The commands above should work unchanged in your WSL shell. If you need to call it from a Windows terminal, use the \\wsl$\Ubuntu\home\austin\projects\Scribe style paths.

That’s it. Set the environment variables, smoke‑test the server, register it with Codex via codex mcp add or config.toml, and verify with /mcp in the Codex TUI. Once it’s hooked up, you can start logging and updating docs across your codebases. Go forth and build your Frankenstein of subprojects—Scribe will keep the mess slightly less messy.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured