REPOGEO REPORT · LITE

zilliztech/memsearch

Default branch main · commit 03b0d026 · scanned 5/13/2026, 2:41:53 PM

GitHub: 1,679 stars · 159 forks

AI VISIBILITY SCORE

40 /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

3 / 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 zilliztech/memsearch, 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

Reposition the README's opening statement to clarify its role

Why:

CURRENT

<p align="center"> <strong>Cross-platform semantic memory for AI coding agents.</strong> </p>

COPY-PASTE FIX

<p align="center"> <strong>A persistent, unified memory layer for all your AI agents, designed specifically for agent context and long-term recall, distinct from general-purpose vector databases.</strong> </p>

mediumtopics#2

Add more specific AI agent memory topics

Why:

CURRENT

agent, agent-memory, ai-agents, claude-code, claude-code-plugin, codex, codex-cli, embeddings, harness, hybrid-search, long-term-memory, memory, milvus, openclaw, opencode, progressive-disclosure, rag, reranker, semantic-search, skills

COPY-PASTE FIX

agent, agent-memory, ai-agents, claude-code, claude-code-plugin, codex, codex-cli, embeddings, harness, hybrid-search, long-term-memory, memory, milvus, openclaw, opencode, progressive-disclosure, rag, reranker, semantic-search, skills, agent-orchestration, ai-agent-framework, agent-context-management

lowreadme#3

Add a 'Comparison with Vector Databases' section to README

Why:

COPY-PASTE FIX

## memsearch vs. Vector Databases
While memsearch leverages vector search capabilities (e.g., via Milvus), it is fundamentally an **AI agent memory layer** designed for persistent context, cross-platform recall, and agent-specific RAG, rather than a general-purpose vector database.

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 zilliztech/memsearch

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

milvus-io/milvus

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

milvus-io/milvus · recommended 2×
Pinecone · recommended 2×
pgvector/pgvector · recommended 2×
chroma-core/chroma · recommended 2×
weaviate/weaviate · recommended 2×

CATEGORY QUERY
How can I implement a unified, persistent memory layer for multiple AI coding agents?
you: not recommended
AI recommended (in order):
1. Milvus (milvus-io/milvus)
2. Pinecone
3. Redis (redis/redis)
4. RedisJSON (RedisJSON/RedisJSON)
5. RediSearch (RediSearch/RediSearch)
6. PostgreSQL
7. pgvector (pgvector/pgvector)
8. Elasticsearch (elastic/elasticsearch)
9. Chroma (chroma-core/chroma)
10. Weaviate (weaviate/weaviate)
AI recommended 10 alternatives but never named zilliztech/memsearch. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools help provide long-term semantic memory and RAG capabilities for AI agents?
you: not recommended
AI recommended (in order):
1. Pinecone
2. Weaviate (weaviate/weaviate)
3. Qdrant (qdrant/qdrant)
4. Chroma (chroma-core/chroma)
5. Faiss (facebookresearch/faiss)
6. Milvus (milvus-io/milvus)
7. PostgreSQL with `pgvector` (pgvector/pgvector)
AI recommended 7 alternatives but never named zilliztech/memsearch. 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 zilliztech/memsearch?
pass
AI named zilliztech/memsearch explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts zilliztech/memsearch in production, what risks or prerequisites should they evaluate first?
pass
AI named zilliztech/memsearch 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 zilliztech/memsearch solve, and who is the primary audience?
pass
AI named zilliztech/memsearch explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of zilliztech/memsearch. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/zilliztech/memsearch.svg)](https://repogeo.com/en/r/zilliztech/memsearch)

HTML

<a href="https://repogeo.com/en/r/zilliztech/memsearch"><img src="https://repogeo.com/badge/zilliztech/memsearch.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

zilliztech/memsearch — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite