A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
16 ★ · grooverLab/fable · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 16 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository grooverLab/fable;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Your Claude already has a memory. fable unlocks it. **Quickstart** · **Why fable** · **Benchmarks** · **Roadmap** · **Discussions** Every conversation you've ever had with Claude Code is already saved on your machine — every decision, every debugging hunt, every 2 AM breakthrough, word for word. **Claude just isn't allowed to use it.** Mid-session, compaction builds a wall: everything behind it is locked away to save tokens, and Claude carries on with a thin summary. /clear wipes the slate. And after 30 days, Claude Code quietly **deletes the files themselves**. Your project's real memory — locked, then destroyed, by design. Everyone else sells you a *replacement* memory: summaries, extracted facts, vector stores. fable does something different — **it unlocks the real one.** 100% local · no API keys · no cloud · no daemons. Your conversations never leave your machine. Setup & commands fable install is idempotent — safe to re-run; it skips anything already wired. To do it by hand: fable setup (home) · claude mcp add fable -- fable mcp (MCP) · fable discover (index). | command | what it does | |---|---| | fable search | rank threads by relevance (--project, --kind, -n) | | fable context | assemble a budgeted context pack | | fable thread | a thread's raw turns, byte-identical | | fable file | a file's full edit history across sessions | | fable cards run | generate AI summary cards (background) | | fable discover | (re)scan + index all Claude Code projects | | fable prune · fable export · fable stats | slim a session · export · index stats | | fable serve | the dashboard | - **Ask about past conversations with Claude — get the real answer.** *"What did we decide about auth last month?"* Claude searches its own history mid-session (via MCP) and quotes the **actual transcript** — not a summary, not an extracted "fact." The conversation itself. - **The wall stops costing you.** fable catalogs everything before compaction walls it off, and hands back exactly what Claude lost — on demand, under a token budget you set. - **The 30-day deletion becomes irrelevant.** Sealed into a local vault, byte-identical, for as long as you decide. First of its kind — five things no other tool does 🧵 **Composed Sessions.** Hand-pick conversations from *any* project, any month — put them in *your* order — and fable builds a brand-new session that Claude resumes as its own lived history. A workspace with curated memory. *(Empirically verified: restitched sessions resume cleanly, signatures intact.)* 🕰️ **File time-travel.** Your transcripts accidentally versioned everything. fable reconstructs **every file's edit history** — every Edit and Write Claude ever made, across every session — with side-by-side comparison between any two moments of a file's life, and a jump back to the conversation that made each change. (fable file src/loader.py) ✂️ **Transcript Surgery.** Your 80 MB session is paying rent on dead threads. Remove whole conversations — fable re-stitches the timeline, shows you the simulation first, and keeps every removed byte recallable forever. Reversible by construction. 🪶 **Pruning that loses nothing.** Slim every message (tool noise, images, bloat) before resuming a heavy session — with an itemized preview of the