MCP Proxy Monorepo

MCP Proxy Monorepo

Monorepo for MCP (Model Control Protocol) servers enabling AI integrations.

View on GitHub
13
Stars
2
Forks
13
Watchers
1
Issues
MCP Proxy Monorepo provides servers implementing the Model Control Protocol (MCP) for integrating AI services, particularly through Bitte AI. It offers a structured framework for hosting and developing MCP-compliant server packages and supports scalable, multi-service deployments. The project is built using Bun for the JavaScript runtime, Turborepo for monorepo management, and includes tools for development, code quality, and package extensibility.

Key Features

Implements Model Control Protocol for AI services
Supports multiple MCP server packages
Centralized configuration via monorepo structure
Integration with Bitte AI services
Uses Bun as JavaScript runtime
Turborepo for monorepo management
Built-in development scripts
Code formatting and linting with Biome
Customizable package addition
Server endpoint for MCP protocol access

Use Cases

Deploying standardized MCP servers for AI model integrations
Extending MCP server capabilities with custom packages
Centralized management of multiple AI service endpoints
Integrating Bitte AI into broader application workflows
Rapid prototyping and development of MCP-based services
Managing model context across distributed AI deployments
Implementing MCP protocol in custom AI pipelines
Ensuring code quality in multi-service environments
Providing a unified interface for diverse AI backend services
Enabling scalable AI model operations via protocol-standard interfaces

README

MCP Proxy Monorepo

This monorepo contains MCP (Model Control Protocol) servers for different services.

Server URI

https://mcp.bitte.ai/sse

Add to Curser Settings

{
  "mcpServers": {
    "bitte-ai": {
      "url": "https://mcp.bitte.ai/sse"
    }
  }
}

Packages

  • bitte-ai: MCP server for Bitte AI integrations

Setup

To install dependencies:

bash
bun install

Development

This project uses Turborepo for managing the monorepo workflow and Biome for code quality tools.

Build all packages

bash
bun run build

Start both services

bash
bun run start

Development mode

bash
bun run dev

Format and lint your code

bash
bun run check
# To fix automatically:
bun run check:fix

Run individual services

bash
# Run bitte-ai service
bun run dev:bitte-ai

Adding a new package

  1. Create a new directory in the packages folder
  2. Add the necessary package.json, tsconfig.json, and implementation files
  3. Update the root package.json and tsconfig.json to include your new package

This project uses Bun as the JavaScript runtime.

For more information: Vibestreaming Logs

Star History

Star History Chart

Repository Owner

BitteProtocol
BitteProtocol

Organization

Repository Details

Language TypeScript
Default Branch main
Size 224 KB
Contributors 2
MCP Verified Nov 12, 2025

Programming Languages

TypeScript
97.75%
Dockerfile
2.25%

Tags

server context protocol AI-integration

Join Our Newsletter

Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.

We respect your privacy. Unsubscribe at any time.

Related MCPs

Discover similar Model Context Protocol servers

  • Agentset MCP

    Agentset MCP

    Open-source MCP server for Retrieval-Augmented Generation (RAG) document applications.

    Agentset MCP provides a Model Context Protocol (MCP) server designed to power context-aware, document-based applications using Retrieval-Augmented Generation. It enables developers to rapidly integrate intelligent context retrieval into their workflows and supports integration with AI platforms such as Claude. The server is easily installable via major JavaScript package managers and supports environment configuration for namespaces, tenant IDs, and tool descriptions.

    • ⭐ 22
    • MCP
    • agentset-ai/mcp-server
  • Remote-MCP

    Remote-MCP

    A type-safe, bidirectional system for remote Model Context Protocol communication.

    Remote-MCP provides a simple and secure way to enable remote access to and centralized management of model contexts using the Model Context Protocol. It bridges local MCP clients with remote MCP servers, supporting a modular architecture via tRPC over HTTP. The tool allows integration both as a client and a server, catering to real-time remote access needs ahead of the official MCP roadmap.

    • ⭐ 200
    • MCP
    • ssut/Remote-MCP
  • AtomGit MCP Server

    AtomGit MCP Server

    AI-powered management and automation of AtomGit repositories via the Model Context Protocol.

    AtomGit MCP Server implements the Model Context Protocol to enable AI-driven management and automation of AtomGit open collaboration platform repositories. It offers methods for managing repositories, issues, pull requests, branches, and labels, allowing seamless AI interaction with AtomGit. The server supports integration with platforms like Claude and VSCode, providing a standardized interface for AI to orchestrate complex collaboration workflows. Built with Node.js and easily deployable via npx or from source, it focuses on expanding collaborative capabilities using AI agents.

    • ⭐ 7
    • MCP
    • kaiyuanxiaobing/atomgit-mcp-server
  • Maven Tools MCP Server

    Maven Tools MCP Server

    Universal Maven Central dependency intelligence server for JVM build tools via the Model Context Protocol.

    Maven Tools MCP Server provides an MCP-compliant API delivering rich Maven Central dependency intelligence for JVM build tools like Maven, Gradle, SBT, and Mill. It enables AI assistants to instantly analyze, interpret, and recommend updates, health checks, and maintenance insights by reading maven-metadata.xml directly from Maven Central. With Context7 integration, it supports orchestration and documentation, enabling bulk analysis, stable version filtering, risk assessment, and rapid cached responses. Designed for seamless integration into AI workflows via the Model Context Protocol.

    • ⭐ 14
    • MCP
    • arvindand/maven-tools-mcp
  • Mastra

    Mastra

    A TypeScript framework for building scalable AI-powered agents and applications.

    Mastra is a modern TypeScript-based framework designed for developing AI-powered applications and autonomous agents. It offers model routing to integrate over 40 AI providers, a graph-based workflow engine, advanced context management, and production-ready tools for observability and evaluation. Mastra features built-in support for authoring Model Context Protocol (MCP) servers, enabling standardized exposure of agents, tools, and structured AI resources via the MCP interface.

    • ⭐ 18,189
    • MCP
    • mastra-ai/mastra
  • Parallel Task MCP

    Parallel Task MCP

    Launch deep research or task groups for Parallel APIs via the Model Context Protocol.

    Parallel Task MCP provides a way to initiate and manage research or task groups through LLM clients using the Model Context Protocol. It enables seamless integration with Parallel’s APIs for flexible experimentation and production development. The tool supports both remote and local deployment, and offers connection capabilities for context-aware AI workflows.

    • ⭐ 4
    • MCP
    • parallel-web/task-mcp
    • View all Alternatives

    Didn't find tool you were looking for?

    Be as detailed as possible for better results