RRepoGEO

REPOGEO REPORT · LITE

redis/mcp-redis

Default branch main · commit 49920d7d · scanned 6/11/2026, 1:11:50 AM

GitHub: 528 stars · 98 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 redis/mcp-redis, 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 to clearly state its purpose as a natural language interface for AI agents

    Why:

    CURRENT
    The current README starts with a title and then badges, before getting to the 'Overview' section.
    COPY-PASTE FIX
    Add the following sentence directly after the `# Redis MCP Server` heading: "The official Redis MCP Server is a natural language interface designed for agentic applications to manage and search data in Redis efficiently."
  • mediumtopics#2
    Add more specific topics related to AI agents and natural language processing

    Why:

    CURRENT
    database, genai, llm, mcp, mcp-server, redis
    COPY-PASTE FIX
    database, genai, llm, mcp, mcp-server, redis, ai-agents, natural-language-interface, agentic-ai, llm-orchestration
  • lowreadme#3
    Add a 'Comparison & Ecosystem Fit' section to the README

    Why:

    COPY-PASTE FIX
    Add a new top-level section to the README titled "Comparison & Ecosystem Fit" that explains how Redis MCP Server complements or differs from popular AI agent frameworks (e.g., LangChain, LlamaIndex) and traditional database interaction methods for LLMs.

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 redis/mcp-redis
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. OpenAI API · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. Microsoft Semantic Kernel · recommended 1×
  • CATEGORY QUERY
    How to build AI agent applications that interact with databases using natural language?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI API
    4. Hugging Face Transformers
    5. Microsoft Semantic Kernel
    6. SQLCoder
    7. DB-GPT

    AI recommended 7 alternatives but never named redis/mcp-redis. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools facilitate LLM-driven data management operations like caching and session storage?
    you: not recommended
    AI recommended (in order):
    1. Redis
    2. Memcached
    3. Vespa.ai
    4. MongoDB
    5. PostgreSQL
    6. Amazon DynamoDB
    7. Google Cloud Firestore
    8. Azure Cosmos DB
    9. Elasticsearch

    AI recommended 9 alternatives but never named redis/mcp-redis. 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 redis/mcp-redis?
    pass
    AI named redis/mcp-redis explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts redis/mcp-redis in production, what risks or prerequisites should they evaluate first?
    pass
    AI named redis/mcp-redis 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 redis/mcp-redis solve, and who is the primary audience?
    pass
    AI named redis/mcp-redis 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 redis/mcp-redis. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/redis/mcp-redis.svg)](https://repogeo.com/en/r/redis/mcp-redis)
HTML
<a href="https://repogeo.com/en/r/redis/mcp-redis"><img src="https://repogeo.com/badge/redis/mcp-redis.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

redis/mcp-redis — 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