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blue-lotus-org/mcp

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Integration two AI's into a modernized MCP for better performance

概览

The LOTUS-MCP protocol outlined here is an impressive approach to , integrating Mistral and Gemini with a structured architecture that allows for: - Routing & fallback strategies between models. - Consensus engine to compare outputs. - Context-aware processing, improving coherence across interactions. - Tool integration, making it extensible for external APIs. - Rate limiting & security for production stability. The Model Context Protocol (MCP) developed by Anthropic for Claude is a groundbreaking open standard that enables AI assistants to connect with external data sources and tools.\ As a developer or business maybe you like to have your own protocol. This guide made for you. Then implement a new modernized structure for MCP. So first thing first is the cost: So to build it we need an architecture design, something like this: This is User Input → Mistral (code/text processing) → Gemini (multimodal enhancement) → Final Output at the final of our journey we can to build.

README

以下为原文 README 节选,完整内容请查看原文。

LOTUS-MCP

FOSS solution

The LOTUS-MCP protocol outlined here is an impressive approach to model coordination and processing, integrating Mistral and Gemini with a structured architecture that allows for:

  • Routing & fallback strategies between models.
  • Consensus engine to compare outputs.
  • Context-aware processing, improving coherence across interactions.
  • Tool integration, making it extensible for external APIs.
  • Rate limiting & security for production stability.

The Model Context Protocol (MCP) developed by Anthropic for Claude is a groundbreaking open standard that enables AI assistants to connect with external data sources and tools.
As a developer or business maybe you like to have your own protocol. This guide made for you.

First looking into MCP exist by claude:

+-------------+     +-------------+     +-------------+
|             |     |             |     |             |
|    User     |     |     AI      |     |   External  |
|  Interface  ||   Model     ||    Tools    |
|             |     |(e.g. Claude)|     |  & Data     |
|             |     |             |     |             |
+-------------+     +-------------+     +-------------+
       ^                   ^                   ^
       |                   |                   |
       |                   |                   |
       v                   v                   v
+--------------------------------------------------+
|                                                  |
|           Model Context Protocol                 |
|                   (MCP)                          |
|                                                  |
+--------------------------------------------------+
       ^                   ^                   ^
       |                   |                   |
       |                   |                   |
       v                   v                   v
+-------------+     +-------------+     +-------------+
|             |     |             |     |             |
| Development |     |  Business   |     |   Content   |
| Environment |     |    Tools    |     | Repositories|
|             |     |             |     |             |
+-------------+     +-------------+     +-------------+

Statement

Then implement a new modernized structure for MCP. So first thing first is the cost:

| Metric          | Mistral Target | Gemini Target |
|-----------------|----------------|---------------|
| Latency         | <800ms         | <1200ms       |
| Accuracy        | 95%            | 92%           |
| Cost/1k tokens  | $0.15          | $0.25         |

So to build it we need an architecture design, something like this:

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│             │     │  Decision   │     │             │
│   User      ├────►│  Router     ├────►│  Mistral    │
在 GitHub 查看完整 README

安装

This server does not publish a one-line install command.

Open the repository installation guide 新手?先看 mcpskill.org 教程 →