agent-skill-memories-off logo
agent-skill-memories-off
★ 48
vs
ogham-mcp logo
ogham-mcp
★ 116

agent-skill-memories-off vs ogham-mcp

agent-skill-memories-off: memories-off provides a minimalist, structured local knowledge management solution that endows agents with long-term memory. It uses standardized Markdown entities and Git-driven workflows to maintain an auditable, rollbackable knowledge base. The project is designed for personal or small project use, with a focus on portability, readability, and flexibility.; ogham-mcp: Ogham MCP is a persistent, searchable shared memory system for AI coding agents that works across different clients and sessions. It stores memories as vector embeddings in PostgreSQL, enabling hybrid search combining semantic and full-text retrieval with high accuracy. Ogham supports multiple embedding providers, knowledge graph traversal, wiki compilation, and automatic memory management features like scoring, condensing, and novelty detection.

01

TL;DR

agent-skill-memories-off logo
agent-skill-memories-offMemory & Context · ★ 48

Personal knowledge management: extract key points from documents and conversations, build a personal knowledge graph

ogham-mcp logo
ogham-mcpMemory & Context · ★ 116

Store and retrieve architectural decisions and coding context across sessions and different AI coding agents

02

Side-by-Side Comparison

Field
agent-skill-memories-off logoagent-skill-memories-off
ogham-mcp logoogham-mcp
Category
Memory & Context
Memory & Context
Stars
★ 48
★ 116
License
Apache-2.0
MIT
Install Command
cd memories-off-skill && python3 scripts/install.py
uvx --from ogham-mcp ogham init
Updated
4mo ago
1w ago
Open Source
Yes
Yes
Tags
agent-skills, cli, llm
agent-memory, ai-memory, claude
03

Features

agent-skill-memories-off logoagent-skill-memories-off
01Lightweight and local-first, no dependency on cloud services
02Structured knowledge via LLM-extracted entities, relations, and observations
03Flexible search by entity name, type, or observation keywords
04Human-readable data with simple backup functionality
ogham-mcp logoogham-mcp
01Persistent shared memory across sessions and clients
02Hybrid search with Reciprocal Rank Fusion (semantic + full-text)
03Knowledge graph with entity linking, traversal, and contradiction detection
04Multi-provider embeddings (OpenAI, Ollama, Mistral, Voyage, Gemini, ONNX)
05Automatic condensing, scoring, novelty detection, and memory lifecycle management
04

Use Cases

agent-skill-memories-off logoagent-skill-memories-off
↳Personal knowledge management: extract key points from documents and conversations, build a personal knowledge graph
↳Personalized content generation: leverage the knowledge graph to generate style-consistent communications or documents
↳Project knowledge base: small teams can use it to accumulate project-level knowledge and optimize agent services
ogham-mcp logoogham-mcp
↳Store and retrieve architectural decisions and coding context across sessions and different AI coding agents
↳Provide consistent, context-aware assistance to AI coding agents by maintaining a shared knowledge base
↳Preserve project-specific information, preferences, and facts for long-term reference without repetition
FAQ

FAQ

What is the difference between agent-skill-memories-off and ogham-mcp?
Both agent-skill-memories-off and ogham-mcp are in the Memory & Context category. agent-skill-memories-off has 48 stars, while ogham-mcp has 116 stars.
Which is better, agent-skill-memories-off or ogham-mcp?
The best choice depends on your use case. Choose agent-skill-memories-off if Personal knowledge management: extract key points from documents and conversations, build a personal knowledge graph, and ogham-mcp if Store and retrieve architectural decisions and coding context across sessions and different AI coding agents.
Is agent-skill-memories-off free or open source?
Yes, agent-skill-memories-off is open source on GitHub (Apache-2.0).
Is ogham-mcp free or open source?
Yes, ogham-mcp is open source on GitHub (MIT).
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