AgentIndex icon
AgentIndex
ContextGraph logo
ContextGraph
★ 22
vs
superlocalmemory logo
superlocalmemory
★ 255

ContextGraph vs superlocalmemory

ContextGraph: ContextGraph is the knowledge layer in the AI agent infrastructure stack. It turns raw agent memories into searchable, governed, tradeable knowledge. It provides a shared memory bus with provenance, impact classification, and multi-protocol support including MCP, A2A, UCP, and real-time streaming.; superlocalmemory: SuperLocalMemory V3 is a local-first AI agent memory system that uses mathematical techniques (differential geometry, algebraic topology, stochastic analysis) to replace cloud LLM dependency. It offers three operating modes, achieves high benchmark scores, and is EU AI Act compliant.

01

TL;DR

ContextGraph logo
ContextGraphRAG / Knowledge Base · ★ 22

Same-company agent follow with provenance and quorum building

Read ContextGraph full review →
superlocalmemory logo
superlocalmemoryRAG / Knowledge Base · ★ 255

IDE integration (Claude Code, Cursor, Windsurf)

Read superlocalmemory full review →
02

Side-by-Side Comparison

Field
ContextGraph logoContextGraph
superlocalmemory logosuperlocalmemory
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 22
★ 255
License
MIT
AGPL-3.0
Install Command
git clone https://github.com/AllenMaxi/ContextGraph.git && cd ContextGraph && python3 -m venv .venv && source .venv/bin/activate && pip install -e ".[server,mcp,dev]"
npm install -g superlocalmemory
Updated
6mo ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
agent-memory, agentic-rag, ai-agents
agent-memory, agent-reliability, ai-agents
03

Features

ContextGraph logoContextGraph
01Provenance Chains with immutable audit trails
02Impact Classification & Quorum Consensus for high-impact claims
03Pattern Subscriptions for graph-native knowledge monitoring
04GitHub-like Dashboard with agent profiles and knowledge browser
05Multi-protocol support (MCP, A2A, UCP) and real-time SSE streaming
superlocalmemory logosuperlocalmemory
015-channel hybrid retrieval (Semantic, BM25, Entity Graph, Temporal, Hopfield)
02Auto-learned soft prompts and adaptive memory lifecycle
03Skill evolution with performance tracking
04Tiered storage (active/warm/cold/archived)
05Trust & Security (Bayesian trust scoring, ABAC, audit trail)
04

Use Cases

ContextGraph logoContextGraph
↳Same-company agent follow with provenance and quorum building
↳Cross-company paid knowledge marketplace with impact-based pricing
↳Entity-aware pattern subscriptions for targeted alerts
superlocalmemory logosuperlocalmemory
↳IDE integration (Claude Code, Cursor, Windsurf)
↳CI/CD pipelines
↳Agent frameworks (OpenClaw, Codex, Goose)
FAQ

FAQ

What is the difference between ContextGraph and superlocalmemory?
Both ContextGraph and superlocalmemory are in the RAG / Knowledge Base category. ContextGraph has 22 stars, while superlocalmemory has 255 stars.
Which is better, ContextGraph or superlocalmemory?
The best choice depends on your use case. Choose ContextGraph if Same-company agent follow with provenance and quorum building, and superlocalmemory if IDE integration (Claude Code, Cursor, Windsurf).
Is ContextGraph free or open source?
Yes, ContextGraph is open source on GitHub (MIT).
Is superlocalmemory free or open source?
Yes, superlocalmemory is open source on GitHub (AGPL-3.0).
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Related

Alternatives to ContextGraph →Alternatives to superlocalmemory →ContextGraph details →superlocalmemory details →