AgentIndex icon
AgentIndex
origin logo
origin
★ 86
vs
ogham-mcp logo
ogham-mcp
★ 116

origin vs ogham-mcp

origin: Origin provides a local memory and knowledge system for AI workflows, enabling agents to recall past context, capture decisions and lessons, and distill them into versioned wiki pages. It uses hybrid retrieval (vector + FTS + graph) and git versioning for auditable, refreshable context.; 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

origin logo
originMemory & Context · ★ 86

Maintaining persistent context across AI work sessions

Read origin full review →
ogham-mcp logo
ogham-mcpMemory & Context · ★ 116

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

Read ogham-mcp full review →
02

Side-by-Side Comparison

Field
origin logoorigin
ogham-mcp logoogham-mcp
Category
Memory & Context
Memory & Context
Stars
★ 86
★ 116
License
Apache-2.0
MIT
Install Command
npx -y @7xuanlu/origin setup
uvx --from ogham-mcp ogham init
Updated
1d ago
1w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent-memory, ai-agents, ai-memory
agent-memory, ai-memory, claude
03

Features

origin logoorigin
01Composition of memories into pages and entity graph linking
02Real git versioning for every memory write
03Mandatory provenance with refreshable wiki pages
04Hybrid retrieval: vector, FTS, and graph context
05Background enrichment, deduplication, and confidence decay
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

origin logoorigin
↳Maintaining persistent context across AI work sessions
↳Capturing and retrieving decisions, lessons, and project facts
↳Distilling related memories into searchable wiki pages
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 origin and ogham-mcp?
Both origin and ogham-mcp are in the Memory & Context category. origin has 86 stars, while ogham-mcp has 116 stars.
Which is better, origin or ogham-mcp?
The best choice depends on your use case. Choose origin if Maintaining persistent context across AI work sessions, and ogham-mcp if Store and retrieve architectural decisions and coding context across sessions and different AI coding agents.
Is origin free or open source?
Yes, origin 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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Related

Alternatives to origin →Alternatives to ogham-mcp →origin details →ogham-mcp details →