REPOGEO REPORT · LITE

Dataojitori/nocturne_memory

Default branch main · commit 93a942d5 · scanned 5/9/2026, 11:12:22 AM

GitHub: 1,045 stars · 129 forks

AI VISIBILITY SCORE

33 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

2 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Dataojitori/nocturne_memory, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Clarify core technology and differentiate from generic databases/RAG in the README intro.

Why:

COPY-PASTE FIX

Insert the following text immediately after the main H1 title: 'Nocturne Memory is a **Python-based, rollbackable, and visual Long-Term Memory Server for MCP Agents**, designed to provide persistent, graph-like structured memory. It is **not a generic database or a vector RAG system**, but a specialized solution to empower AI with identity and memory across models and sessions, serving as a drop-in replacement for OpenClaw.'

mediumtopics#2

Add more specific topics related to AI agents and structured memory.

Why:

CURRENT

agentic-ai, ai-identity, ai-memory, artificial-intelligence, claude, claude-code, digital-soul, gemini-cli, llm, long-term-memory, mcp, mcp-server, postgresql, python, rag, second-brain, sqlite

COPY-PASTE FIX

agentic-ai, ai-identity, ai-memory, artificial-intelligence, claude, claude-code, digital-soul, gemini-cli, llm, long-term-memory, mcp, mcp-server, postgresql, python, rag, second-brain, sqlite, ai-agents, knowledge-graph, agent-memory, llm-memory

lowcomparison#3

Add a 'Comparison' section to differentiate from common alternatives.

Why:

COPY-PASTE FIX

Create a new section titled 'Comparison' or 'Why Nocturne Memory?' that explicitly contrasts Nocturne Memory with: 1. Vector RAG systems (highlighting its structured, graph-like memory and rollback capabilities). 2. Generic databases like PostgreSQL or SQLite (emphasizing its AI-specific features, visual interface, and MCP protocol integration). 3. Other AI agent memory solutions (if applicable, focusing on its rollback, visual audit, and identity features).

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface Dataojitori/nocturne_memory

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

PostgreSQL

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

PostgreSQL · recommended 2×
Neo4j · recommended 1×
Datomic · recommended 1×
SQLite · recommended 1×
Prolog · recommended 1×

CATEGORY QUERY
How to implement persistent, structured long-term memory for AI agents without vector RAG?
you: not recommended
AI recommended (in order):
1. Neo4j
2. PostgreSQL
3. Datomic
4. SQLite
5. Prolog
6. Apache Jena
AI recommended 6 alternatives but never named Dataojitori/nocturne_memory. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What framework provides a rollbackable server for AI agent memory across sessions and models?
you: not recommended
AI recommended (in order):
1. LangChain
2. Weaviate
3. Milvus
4. Pinecone
5. LlamaIndex
6. PostgreSQL
7. pg_trgm
8. MongoDB
9. CockroachDB
10. Apache Cassandra
11. Temporal.io
AI recommended 11 alternatives but never named Dataojitori/nocturne_memory. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of Dataojitori/nocturne_memory?
pass
AI named Dataojitori/nocturne_memory explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts Dataojitori/nocturne_memory in production, what risks or prerequisites should they evaluate first?
pass
AI named Dataojitori/nocturne_memory explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo Dataojitori/nocturne_memory solve, and who is the primary audience?
pass
AI did not name Dataojitori/nocturne_memory — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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Brand-free category queries5 vs 2 in Lite
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