What is the primary purpose of Daem0n-MCP?

It provides a persistent memory layer for Claude, allowing it to remember decisions, code patterns, and project context across different sessions and repositories.

How do I share memory between a client and server repository?

You can use the 'Option A' approach by navigating to a common parent directory, initializing Daem0n there, and using link_projects and consolidate_linked_databases to merge the child repositories' histories.

What is the Silent Scribe feature?

The Silent Scribe uses hooks in your .claude/settings.json to automatically capture and log decisions, warnings, and changes as you work, without requiring manual input.

When should I use condensed visions?

Use condensed visions (condensed=True) when you need to survey a large number of memories quickly or get a broad overview of the project's history without deep detail.

Daem0n MCP Context Manager

Name: Daem0n MCP Context Manager
Author: DasBluEyedDevil

byDasBluEyedDevil

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Productivity & Workflow

Manages persistent project memory and cross-repository context for seamless Claude coding sessions.

About

The Daem0n-MCP skill provides a robust framework for initializing and consolidating project context across complex directory structures. It enables Claude to maintain a persistent memory of architectural decisions, failed paths, and code patterns, even when working across multiple repositories. By utilizing automated hooks like the Silent Scribe and advanced indexing features, this skill ensures that Claude remains aware of your project's history, significantly reducing context window fatigue and improving the accuracy of generated code through hybrid vector search and incremental indexing.

Key Features

Incremental code indexing and parse tree caching for high performance
36 GitHub stars
Multi-repo context linking and database consolidation for complex projects
Hybrid vector and TF-IDF search for high-fidelity memory recall
Detailed health insights including entity counts and indexing status
Silent Scribe automated decision logging via Pre/Post-tool hooks

Use Cases

Synchronizing context between a frontend and backend repository in a microservices architecture
Optimizing context retrieval in large-scale codebases using condensed memory visions
Automatically tracking and recalling historical architectural decisions without manual documentation

About

Key Features

Incremental code indexing and parse tree caching for high performance
36 GitHub stars
Multi-repo context linking and database consolidation for complex projects
Hybrid vector and TF-IDF search for high-fidelity memory recall
Detailed health insights including entity counts and indexing status
Silent Scribe automated decision logging via Pre/Post-tool hooks

Use Cases

Synchronizing context between a frontend and backend repository in a microservices architecture
Optimizing context retrieval in large-scale codebases using condensed memory visions
Automatically tracking and recalling historical architectural decisions without manual documentation