RRepoGEO

REPOGEO REPORT · LITE

rdragos/awesome-mpc

Default branch main · commit 18b3f86e · scanned 5/25/2026, 10:27:53 AM

GitHub: 1,975 stars · 281 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 rdragos/awesome-mpc, 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 README opening to emphasize 'awesome list' type

    Why:

    CURRENT
    Multiparty computation (MPC) allows several parties to jointly compute on secrets without revealing them. This list is designed to be a central place where everyone can find open-source software designed for MPC as well as introductory material to this topic.
    COPY-PASTE FIX
    This is an awesome list dedicated to Multi-Party Computation (MPC), a field that allows several parties to jointly compute on secrets without revealing them. It serves as a central hub for open-source MPC software and introductory materials.
  • hightopics#2
    Add 'awesome-list' topic

    Why:

    CURRENT
    crypto, multiparty-computation, secure-computation
    COPY-PASTE FIX
    crypto, multiparty-computation, secure-computation, awesome-list
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).

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 rdragos/awesome-mpc
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MP-SPDZ
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. MP-SPDZ · recommended 2×
  2. SCALE-MAMBA · recommended 2×
  3. Concrete-ML · recommended 1×
  4. EMP-toolkit · recommended 1×
  5. libOTe · recommended 1×
  • CATEGORY QUERY
    Where can I find open-source libraries for secure multi-party computation development?
    you: not recommended
    AI recommended (in order):
    1. MP-SPDZ
    2. Concrete-ML
    3. SCALE-MAMBA
    4. EMP-toolkit
    5. libOTe
    6. aby

    AI recommended 6 alternatives but never named rdragos/awesome-mpc. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best frameworks and tools for learning multi-party computation concepts?
    you: not recommended
    AI recommended (in order):
    1. MP-SPDZ
    2. FHE-SPDZ
    3. SCALE-MAMBA
    4. ABY
    5. MOTION
    6. Obliv-C
    7. Sharemind

    AI recommended 7 alternatives but never named rdragos/awesome-mpc. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 rdragos/awesome-mpc?
    pass
    AI did not name rdragos/awesome-mpc — 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?

  • If a team adopts rdragos/awesome-mpc in production, what risks or prerequisites should they evaluate first?
    pass
    AI named rdragos/awesome-mpc 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 rdragos/awesome-mpc solve, and who is the primary audience?
    pass
    AI named rdragos/awesome-mpc 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 rdragos/awesome-mpc. 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/rdragos/awesome-mpc.svg)](https://repogeo.com/en/r/rdragos/awesome-mpc)
HTML
<a href="https://repogeo.com/en/r/rdragos/awesome-mpc"><img src="https://repogeo.com/badge/rdragos/awesome-mpc.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

rdragos/awesome-mpc — 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