00 } ``` ## Development 🔧 - `npm run lint`: Run ESLint - `npm run format`: Format code with Prettier - `npm run clean`: Clean build artifacts - `npm run build`: Build the project ## Contributing PRs welcome! Help us make AI workflows less dumb. --- ## License MIT — do whatever, just don't be evil. --- Made with ❤️ by [Pink Pixel](https://pinkpixel.dev)25:T5d4,## What is MindBridge MCP? MindBridge MCP is an AI orchestration server that enables seamless communication between various applications and large language models (LLMs) like OpenAI, Anthropic, and DeepSeek through a unified API. ## How to use MindBridge MCP? To use MindBridge, install it via npm or clone the repository from GitHub. Configure your API keys for the desired LLMs, and start the server to begin routing queries and managing workflows. ## Key features of MindBridge MCP? - Multi-LLM support for easy switching between different models. - Smart routing to models optimized for deep reasoning tasks. - Built-in tool for comparing responses from multiple models. - OpenAI-compatible API layer for easy integration. - Automatic detection of providers for hassle-free setup. - Highly configurable through environment variables and JSON. ## Use cases of MindBridge MCP? 1. Building multi-model AI workflows. 2. Orchestrating complex reasoning tasks across different LLMs. 3. Creating AI-powered applications without vendor lock-in. 4. Facilitating second opinions by querying multiple models. ## FAQ from MindBridge MCP? - Can MindBridge connect to any LLM? > Yes! MindBridge supports a variety of LLMs including OpenAI, Anthropic, and more. - Is there a cost to use MindBridge? > MindBridge is open-source and free to use under the MIT license. - How do I configure MindBridge? > Configuration is done through environment variables and a JSON file for MCP settings.26:T23aa,

GitHub Second Brain

A set of tools that strategically extract only the key information from any codebases, so your AI actually has enough context to assist you.
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## Project Launch

## Why? ### The Problem Even senior developers struggle with large, unfamiliar, interconnected codebases and their dependencies. For AI, this is even a bigger problem because without enough context, AI can't help, and will hallucinate but with too much, it will exceed its capability (context window limits). ### Solution This project develops tools for targeted, on-demand data extraction from diverse raw code repositories. It aims to provide AI clients (LLMs) with concise, query-relevant context/data to enhance understanding of unfamiliar or multiple codebases. This effectively manages token limits problem while complementing other existing AI tools. ## ✨ Features * 😎 **Latest Documentation on ANY GitHub Project**: Grant your AI assistant seamless access to the GitHub project's documentation and code. The built-in retrieval tools help the AI gets tree directory and specific file content without exceeding Context Window Limit! * 🧠 **No More Hallucinations**: With Github Second Brain, your AI assistant can provide accurate and relevant answers to your questions. *

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MindBridge MCP Server ⚡ The AI Router for Big Brain Moves

Github Second Brain