montycat-mcp logo
montycat-mcp
★ 28
vs
okf-agent-memory logo
okf-agent-memory
★ 827

montycat-mcp vs okf-agent-memory

montycat-mcp: Montycat MCP is a self-hosted server that provides AI agents with persistent, searchable memory, enabling them to retain context and decisions across sessions. It supports various Model Context Protocol clients, allowing multiple agents to read from and write to a single shared memory store with hybrid search capabilities.; okf-agent-memory: OKF Agent Memory provides a domain-neutral, Git-native persistent project memory for AI agents, leveraging the Dual-Memory Agent Architecture to prevent context bloat and memory rot. It uses an ultra-compact behavioral codex and a queryable OKF v0.2 knowledge bundle, with blazing-fast, zero-cost local retrieval.

01

TL;DR

montycat-mcp logo
montycat-mcpMemory & Context · ★ 28

Storing and recalling team decisions and preferences

okf-agent-memory logo
okf-agent-memoryMemory & Context · ★ 827

Software Engineering: Managing architecture decisions, code references, and operational constraints.

02

Side-by-Side Comparison

Field
montycat-mcp logomontycat-mcp
okf-agent-memory logookf-agent-memory
Category
Memory & Context
Memory & Context
Stars
★ 28
★ 827
License
MIT
MIT
Install Command
pip install montycat-mcp
git clone https://github.com/okf-memory/okf-agent-memory.git && cd okf-agent-memory && make build
Updated
2w ago
1d ago
Open Source
Yes
Yes
Tags
AI Agents, Shared Memory, Persistent Memory
AI Agents, Persistent Memory, Knowledge Base
03

Features

montycat-mcp logomontycat-mcp
01Persistent memory across chat sessions
02Single shared memory for multiple AI agents
03Hybrid search (vector, keyword, BM25) for recall
04Self-hosted server, engine, and embeddings
okf-agent-memory logookf-agent-memory
01Dual-Memory Cognitive Architecture (DMAA) to eliminate prompt bloat.
02Blazing fast performance with in-memory BM25 search (<300µs) and graph validation (~4ms).
03100% Git-native, zero vendor lock-in, and zero API costs for memory retrieval.
04Built on Google's Open Knowledge Format (OKF) v0.2 for standardized agent knowledge.
05Solves context bloat and memory rot through progressive disclosure and Search-Before-Write principle.
04

Use Cases

montycat-mcp logomontycat-mcp
↳Storing and recalling team decisions and preferences
↳Maintaining project context and progress across AI agent interactions
↳Facilitating collaboration among multiple AI agents through shared scopes
↳Providing persistent knowledge base for AI assistants
okf-agent-memory logookf-agent-memory
↳Software Engineering: Managing architecture decisions, code references, and operational constraints.
↳Scientific Research & Literature Reviews: Organizing and querying research findings and insights.
↳Coaching & Operations: Storing client session history, ethical guidelines, and runbooks.
↳Multi-Agent Collaboration: Providing a shared, auditable knowledge base for autonomous agents.
05

Best For

montycat-mcp logomontycat-mcp
—
okf-agent-memory logookf-agent-memory
Hidden Gem
FAQ

FAQ

What is the difference between montycat-mcp and okf-agent-memory?
Both montycat-mcp and okf-agent-memory are in the Memory & Context category. montycat-mcp has 28 stars, while okf-agent-memory has 827 stars.
Which is better, montycat-mcp or okf-agent-memory?
The best choice depends on your use case. Choose montycat-mcp if Storing and recalling team decisions and preferences, and okf-agent-memory if Software Engineering: Managing architecture decisions, code references, and operational constraints..
Is montycat-mcp free or open source?
Yes, montycat-mcp is open source on GitHub (MIT).
Is okf-agent-memory free or open source?
Yes, okf-agent-memory is open source on GitHub (MIT).
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