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Emojikey MCP Server

MCP Server

Persist emoji‑based LLM interaction styles across devices

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Updated Sep 23, 2025

About

The Emojikey MCP Server stores and manages emoji‑based context keys (emojikeys) for LLMs, enabling consistent interaction styles across conversations and devices without storing personal data. It offers APIs to get, set, and view emojikey history.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Overview

The Mcp Server Emojikey is a lightweight MCP server that turns relationship context into emoji‑based memory keys. By storing a compact, human‑readable key that represents the conversational tone, preferences, and prior interactions, Claude can persist a consistent “vibe” across sessions without retaining sensitive user data. This approach is particularly valuable for developers building AI assistants that need to maintain a personality or contextual awareness while respecting privacy constraints.

What Problem Does It Solve?

Traditional context‑management systems rely on bulky text logs or database tables that grow linearly with conversation length. They can become difficult to cache, transmit, and interpret across devices. Emojikeys condense a user’s conversational history into a single emoji string that captures mood, style, and key topics. Developers can now store, retrieve, and share these keys via a simple API, ensuring that the assistant’s tone remains stable even when users switch devices or start new threads.

Core Functionality and Value

  • Persisted Context: Each emojikey is stored online, allowing cross‑device synchronization without exposing personal data.
  • Dynamic Aggregation: The server can generate aggregated keys for various time windows (lifetime, 90‑day, 30‑day, etc.), giving developers granular control over how much historical context influences a new session.
  • Minimal Payload: Because the key is just an emoji string, network traffic and storage requirements are negligible compared to full transcript logs.
  • Developer‑Friendly Tools: The server exposes a set of MCP tools—, , , , and —that can be invoked directly from Claude or any MCP‑compatible client.

Use Cases and Real‑World Scenarios

  • Personal Assistants: A mobile AI helper can remember a user’s preferred tone (e.g., friendly, formal) across sessions without storing the entire chat history.
  • Customer Support Bots: By aggregating recent interactions, a bot can quickly adapt to the current customer’s sentiment and context.
  • Educational Tutors: An AI tutor can maintain a consistent pedagogical style, reflecting past lessons in the emojikey.
  • Creative Writing Aids: Writers can set a “vibe” key to keep the assistant’s suggestions aligned with their current mood or genre.

Integration into AI Workflows

Developers integrate the server by adding it to their MCP configuration, supplying an API key from emojikey.io and optionally a model ID. During the first conversation, the assistant is instructed to “Set emojikey”; subsequent sessions automatically pull the stored key. The server’s tools can be called at any point to refresh or modify the key, enabling dynamic adaptation during a dialogue. Because the keys are stored remotely and anonymized, they can be shared across teams or persisted in cloud storage with minimal compliance overhead.

Unique Advantages

  • Privacy‑First Design: No user text is stored—only emoji tokens, making compliance with data protection regulations straightforward.
  • Cross‑Platform Consistency: A single key works everywhere, from desktop to mobile to web assistants.
  • Scalable Context Management: Aggregated keys let developers decide how much history to incorporate, balancing performance and relevance.
  • Extensibility: The optional coding mode (via ) opens the door to richer, code‑aware interactions without compromising core privacy guarantees.

In summary, the Mcp Server Emojikey offers a lightweight, privacy‑preserving mechanism for maintaining conversational context. By leveraging emoji tokens as memory keys, developers can deliver consistent AI experiences across devices while keeping data footprints minimal and compliant.