bvandeusen
6aa84002b3
MCP clients see tools namespaced by the server's local name already
(mcp__<server>__<tool>), so the fable_ prefix on every tool name was
redundant and ate tokens in the model's tool list.
Tools renamed (34 total):
fable_search → search
fable_list_notes / get_note / create_note / update_note / delete_note → list_notes / ...
fable_list_tasks / get_task / create_task / update_task / add_task_log → list_tasks / ...
fable_list_projects / get_project / create_project / update_project → list_projects / ...
fable_list_milestones / create_milestone / update_milestone → list_milestones / ...
fable_list_events / create_event / get_event / update_event / delete_event → list_events / ...
fable_list_tags → list_tags
fable_get_recent → get_recent
fable_list_persons / create_person / update_person → list_persons / ...
fable_list_places / create_place / update_place → list_places / ...
fable_list_lists / create_list / update_list → list_lists / ...
Also rebranded in MCP scope:
FastMCP("fable", ...) → FastMCP("scribe", ...)
auth realm "fable-mcp" → "scribe-mcp"
ASGI scope key fable_user_id → scribe_user_id
ContextVar label fable_mcp_user_id → scribe_mcp_user_id
Tool docstrings "in Fable" / "Fable task" → "in Scribe" / "Scribe task"
Server _INSTRUCTIONS prose
Deliberately kept:
- The internal Python package name `fabledassistant` (per project naming
convention — internal stays).
- "Fabled Scribe" as the official product/brand name (page footer,
smtp_from_name default).
- References to the legacy `fable-mcp/` standalone package in docstrings
explaining what we ported from — accurate until that directory is
deleted in Phase 10.
Client impact: existing MCP registrations need
claude mcp remove <name> && claude mcp add ...
once with a freshly-copied snippet from Settings → MCP Access. Claude
Code then re-discovers tools on connect — old conversations that
referenced fable_* tool names will see "tool not found" on those calls
until updated.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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, an MCP server for external AI clients, and an Android companion app.
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.ymlto 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 |
| Android App | Flutter companion app architecture and feature status |
License
This project is privately maintained.