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grooverLab/fable

by Various

High-fidelity transcript memory for Claude Code — index every session, recall byte-identical, search, prune, compose. Local-first, stdlib-only, MCP.

G

MCP

grooverLab/fable

Added 18 June 2026

#agent-memory #ai-memory #anthropic #claude #claude-code #cli #developer-tools #llm

Overview

Fable provides high-fidelity transcript memory for Claude Code. It indexes every session and allows byte-identical recall, search, pruning, and composition. The tool is local-first, uses only the Python standard library, and supports the Model Context Protocol (MCP).

Best for

Best for
Developers who need local, high-fidelity transcript memory specifically for Claude Code sessions.

Use cases

  • Index and recall Claude Code transcripts exactly.
  • Search through session history locally.
  • Prune or compose transcripts for downstream use.

How to use

Install

pipx install git+https://github.com/grooverLab/fable && fable install

Tools exposed

  • pipx
  • fable

Tested with

Claude Code

Notes

Fable provides high-fidelity transcript memory for Claude Code. It indexes every session and allows byte-identical recall, search, pruning, and composition. The tool is local-first, uses only the Python standard library, and supports the Model Context Protocol (MCP).

2 stars on GitHub. Last updated 2026-06-18. Licensed MIT.

Use cases

  • Index and recall Claude Code transcripts exactly.
  • Search through session history locally.
  • Prune or compose transcripts for downstream use.

Pros

  • Local-first architecture keeps all data on your machine.
  • Stdlib-only dependencies simplify installation and avoid conflicts.
  • MCP support enables integration with other tools.

Cons

  • Very limited adoption with only 2 GitHub stars suggests a small or inactive community.
  • No external dependencies may limit advanced features compared to richer alternatives.
  • Designed specifically for Claude Code, not general-purpose transcript management.

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Local-first architecture keeps all data on your machine.
  • Stdlib-only dependencies simplify installation and avoid conflicts.
  • MCP support enables integration with other tools.

Cons

  • Very limited adoption with only 2 GitHub stars suggests a small or inactive community.
  • No external dependencies may limit advanced features compared to richer alternatives.
  • Designed specifically for Claude Code, not general-purpose transcript management.

Pairs with

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