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feat(mcp): make Scribe reflexively recall + scope reads to the active project
The MCP surface advertised writing well but recall poorly, and project
scoping had no anchor that survived past enter_project's snapshot:

- search / list_notes dropped the project_id their services already
  support, so a scoped search was impossible — every query swept all
  projects and bled unrelated work into the session.
- The tool descriptions were mechanical ("Semantic search over the
  user's notes and tasks") with no trigger telling Claude WHEN to reach
  for them; the server instructions were all write-discipline and said
  nothing about searching before answering or starting work.

Changes:
- search, list_notes: add project_id param, wired to the service.
- search, list_notes, list_tasks: trigger-worded descriptions that push
  passing the active project's id and reserve project_id=0 for a
  deliberate cross-project sweep.
- _INSTRUCTIONS: add a 'Reach for Scribe to RECALL, not just to record'
  block — search before answering/starting, check for an existing ticket
  before create_task, scope reads to the active project (which does not
  stick on the server).

Paired with always-on rule #75 in the FabledSword-family rulebook.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 22:43:55 -04:00

Fabled Scribe

A self-hosted second brain and project management application with integrated LLM capabilities. Write, organise, and act on your notes and tasks with the help of a local AI assistant — all running on your own hardware.

Features

Notes and tasks with a Markdown editor, sub-tasks, milestones, and kanban project workspaces. AI chat with streaming responses, RAG over your notes, and tool use (web search, calendar, weather). A daily briefing that digests your tasks, RSS feeds, and weather on a schedule. Knowledge graph, per-user/group sharing, PWA with push notifications, and an MCP server for external AI clients.

Quick Start

Prerequisites: Docker and Docker Compose. 8 GB+ RAM recommended for LLM inference.

Download docker-compose.quickstart.yml from this repo, then:

# Optional but recommended — set a secret key
export SECRET_KEY=your-random-secret-here

docker compose -f docker-compose.quickstart.yml up -d

Open http://localhost:5000. The first user to register becomes admin. Go to Settings → General to pull an LLM model — qwen3:8b or llama3.1:8b are good starting points.

GPU: Ollama runs CPU-only by default. See the comments in docker-compose.quickstart.yml to enable NVIDIA GPU passthrough.

Development: To build from source, see Development.

Documentation

Doc Contents
Architecture Stack, design decisions, data models, key services
Configuration Environment variables, Docker Compose, production setup, security
Features Detailed feature breakdown and keyboard shortcuts
Development Dev workflow, CI/CD, migrations, release process
API Keys & MCP API key management and Fable MCP install guide
SSO / OAuth OIDC setup for Authentik, Keycloak, and other providers
API Reference All REST API endpoints

License

This project is privately maintained.

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