AgentIndex icon
AgentIndex
AgentRecall-X logo
AgentRecall-X
★ 371
vs
state-memory-mcp logo
state-memory-mcp
★ 49

AgentRecall-X vs state-memory-mcp

AgentRecall-X: AgentRecall is a unique agent memory system that not only stores human corrections but also measures whether these corrections lead to actual behavioral changes in the agent across sessions. It provides a governed corrections ledger and a measurement harness to track and verify if an agent stops repeating past mistakes.; state-memory-mcp: @putervision/state-memory-mcp is a zero-infrastructure, deterministic Model Context Protocol (MCP) server designed to provide AI coding assistants with a structured, persistent SQLite graph for tracking workflow state. It offers efficient context management, reduces latency by offloading to a local database, and supports multi-agent collaboration with a shared blackboard.

01

TL;DR

AgentRecall-X logo
AgentRecall-XMemory & Context · ★ 371

Ensuring AI agents learn from past mistakes and avoid repeating errors across sessions.

Read AgentRecall-X full review →
state-memory-mcp logo
state-memory-mcpMemory & Context · ★ 49

Providing persistent workflow state to AI coding assistants like Cursor and Copilot

Read state-memory-mcp full review →
02

Side-by-Side Comparison

Field
AgentRecall-X logoAgentRecall-X
state-memory-mcp logostate-memory-mcp
Category
Memory & Context
Memory & Context
Stars
★ 371
★ 49
License
MIT
MIT
Install Command
claude mcp add --scope user agent-recall -- npx -y agent-recall-mcp
npm install -g @putervision/state-memory-mcp && state-memory-mcp init
Updated
1w ago
2w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Agent Memory, LLM Learning Loop, Correction Tracking
State Management, Context Management, SQLite
03

Features

AgentRecall-X logoAgentRecall-X
01Governed corrections ledger with severity, evidence, and outcome tracking.
02Unique measurement of behavioral change, tracking if agents stop repeating mistakes.
03Five distinct memory layers (episodic, semantic, procedural, narrative, correction) for comprehensive context.
04Local-first semantic recall using an ONNX embedding model for privacy and offline capability.
05Automated session loop for context loading and saving, plus nightly consolidation ('Dreaming').
state-memory-mcp logostate-memory-mcp
01Deterministic State Memory & Compact TaskSlices for fast evaluation
02Efficient Context Management & Decision Thresholding to prevent graph bloat
03Multi-Agent Blackboard for shared context and parallel subagent updates
04100% Local & Private architecture, ensuring all state stays within your workspace
05Interactive 3D Visualizer for graph exploration
04

Use Cases

AgentRecall-X logoAgentRecall-X
↳Ensuring AI agents learn from past mistakes and avoid repeating errors across sessions.
↳Evaluating agent performance by measuring the effectiveness of corrections and actual behavioral changes.
↳Managing structured, persistent memory for agents, including project context, skills, and past decisions.
↳Integrating agent memory into developer environments (e.g., Claude Code, VS Code) for seamless workflow.
↳Performing private and secure offline semantic search within an agent's knowledge base.
state-memory-mcp logostate-memory-mcp
↳Providing persistent workflow state to AI coding assistants like Cursor and Copilot
↳Managing context and decision-making for autonomous agents
↳Facilitating multi-agent collaboration on complex tasks with a shared context store
↳Auditing and tracing agent activities with a tamper-evident event ledger
↳Improving agent efficiency and reducing latency in task retrieval and context processing
05

Best For

AgentRecall-X logoAgentRecall-X
Hidden Gem
state-memory-mcp logostate-memory-mcp
—
FAQ

FAQ

What is the difference between AgentRecall-X and state-memory-mcp?
Both AgentRecall-X and state-memory-mcp are in the Memory & Context category. AgentRecall-X has 371 stars, while state-memory-mcp has 49 stars.
Which is better, AgentRecall-X or state-memory-mcp?
The best choice depends on your use case. Choose AgentRecall-X if Ensuring AI agents learn from past mistakes and avoid repeating errors across sessions., and state-memory-mcp if Providing persistent workflow state to AI coding assistants like Cursor and Copilot.
Is AgentRecall-X free or open source?
Yes, AgentRecall-X is open source on GitHub (MIT).
Is state-memory-mcp free or open source?
Yes, state-memory-mcp is open source on GitHub (MIT).
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Related

Alternatives to AgentRecall-X →Alternatives to state-memory-mcp →AgentRecall-X details →state-memory-mcp details →