AgentIndex icon
AgentIndex
samyama-graph logo
samyama-graph
★ 184
vs
mcp-memory-libsql logo
mcp-memory-libsql
★ 87

samyama-graph vs mcp-memory-libsql

samyama-graph: Samyama is a graph-vector database written in Rust. It supports OpenCypher queries, Redis protocol, vector search, and graph algorithms. It can handle billions of edges on a single machine.; mcp-memory-libsql: mcp-memory-libsql is a high-performance, persistent memory system for the Model Context Protocol (MCP). It uses libSQL to store entities and relations, providing optimized text search with relevance ranking to enhance LLM context efficiency. It supports both local SQLite and remote libSQL databases with secure authentication.

01

TL;DR

samyama-graph logo
samyama-graphRAG / Knowledge Base · ★ 184

Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.)

Read samyama-graph full review →
mcp-memory-libsql logo
mcp-memory-libsqlRAG / Knowledge Base · ★ 87

Provide persistent memory for LLM applications

Read mcp-memory-libsql full review →
02

Side-by-Side Comparison

Field
samyama-graph logosamyama-graph
mcp-memory-libsql logomcp-memory-libsql
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 184
★ 87
License
Apache-2.0
MIT
Install Command
git clone https://github.com/samyama-ai/samyama-graph && cd samyama-graph && cargo build --release
npx -y mcp-memory-libsql
Updated
1d ago
1d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
billion-edges, cypher, cypher-query-language
ai-tools, embeddings, knowledge-graph
03

Features

samyama-graph logosamyama-graph
01OpenCypher queries
02Redis protocol
03Vector search (HNSW)
04Graph algorithms (PageRank, BFS, etc.)
05Natural language queries (NLQ)
mcp-memory-libsql logomcp-memory-libsql
01High-performance text search with relevance ranking
02Persistent storage of entities and relations
03Flexible text search with fuzzy matching
04Context-optimized for LLM efficiency
05Knowledge graph management
04

Use Cases

samyama-graph logosamyama-graph
↳Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.)
↳Multi-hop graph traversals
↳Cross-knowledge graph aggregation
mcp-memory-libsql logomcp-memory-libsql
↳Provide persistent memory for LLM applications
↳Manage knowledge graphs for context-aware AI
↳Enhance retrieval-augmented generation (RAG) pipelines
FAQ

FAQ

What is the difference between samyama-graph and mcp-memory-libsql?
Both samyama-graph and mcp-memory-libsql are in the RAG / Knowledge Base category. samyama-graph has 184 stars, while mcp-memory-libsql has 87 stars.
Which is better, samyama-graph or mcp-memory-libsql?
The best choice depends on your use case. Choose samyama-graph if Biomedical knowledge graphs (PubMed, ClinicalTrials.gov, etc.), and mcp-memory-libsql if Provide persistent memory for LLM applications.
Is samyama-graph free or open source?
Yes, samyama-graph is open source on GitHub (Apache-2.0).
Is mcp-memory-libsql free or open source?
Yes, mcp-memory-libsql is open source on GitHub (MIT).
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Related

Alternatives to samyama-graph →Alternatives to mcp-memory-libsql →samyama-graph details →mcp-memory-libsql details →