RRepoGEO

REPOGEO REPORT · LITE

IBM/mcp-cli

Default branch main · commit a47fcbeb · scanned 5/22/2026, 10:47:50 AM

GitHub: 1,973 stars · 299 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 IBM/mcp-cli, 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

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

OVERALL DIRECTION
  • highabout#1
    Add a precise 'About' description for LLM CLI functionality

    Why:

    COPY-PASTE FIX
    A powerful command-line interface for interacting with Model Context Protocol servers, enabling seamless communication with LLMs, tool usage, and advanced conversation management with features like AI Virtual Memory.
  • mediumreadme#2
    Add a note clarifying project's independence from IBM Cloud Pak

    Why:

    COPY-PASTE FIX
    Note: While hosted under the IBM organization, this project is an independent open-source initiative focused on Model Context Protocol and LLM interaction, and is not directly related to IBM Cloud Pak deployment or management.

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 IBM/mcp-cli
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. run-llama/llama_index · recommended 2×
  3. openai/openai-python · recommended 2×
  4. microsoft/guidance · recommended 1×
  5. deepset-ai/haystack · recommended 1×
  • CATEGORY QUERY
    How to manage LLM conversations and tool usage from a command line interface locally?
    you: not recommended
    AI recommended (in order):
    1. LangChain CLI / LangChain Expression Language (LCEL) (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. OpenAI Python Library (openai/openai-python)
    4. Guidance (microsoft/guidance)
    5. Haystack (deepset-ai/haystack)
    6. ShellGPT (SGPT) (TheR1D/shell_gpt)
    7. Custom Python Scripting

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

    Show full AI answer
  • CATEGORY QUERY
    What are the best CLI tools for managing long LLM conversation context with virtual memory?
    you: not recommended
    AI recommended (in order):
    1. LangChain CLI (langchain-ai/langchain)
    2. LlamaIndex CLI (run-llama/llama_index)
    3. Ollama (ollama/ollama)
    4. jq (stedolan/jq)
    5. grep
    6. tmux (tmux/tmux)
    7. screen
    8. argparse
    9. Click (pallets/click)
    10. transformers (huggingface/transformers)
    11. openai (openai/openai-python)
    12. faiss-cpu (facebookresearch/faiss)

    AI recommended 12 alternatives but never named IBM/mcp-cli. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    Suggestion:

  • 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 IBM/mcp-cli?
    pass
    AI named IBM/mcp-cli explicitly

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

  • If a team adopts IBM/mcp-cli in production, what risks or prerequisites should they evaluate first?
    pass
    AI named IBM/mcp-cli 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 IBM/mcp-cli solve, and who is the primary audience?
    pass
    AI named IBM/mcp-cli explicitly

    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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IBM/mcp-cli — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite