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MCP Connectors

This is an open - source project that includes over 35 pre - built MCP connectors for integrating SaaS tools into AI applications, supporting local development and type - safe configuration.
Developer toolsArtificial intelligence chatbots#MCP Connectors#SaaS Integration#AI Tools#Open - source Project.TypeScript
2.5 points
4.8K
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Overview

Content Details

Alternatives

What are Disco MCP Connectors?

Disco MCP Connectors is a collection of open - source connectors based on the Model Context Protocol (MCP), specifically designed to provide standardized connections between AI applications and various SaaS tools. It allows developers to easily integrate more than 35 popular tools such as Asana, GitHub, Slack, and Notion into AI applications without having to write complex API integration code from scratch.

How to use Disco MCP Connectors?

There are two main ways to use them: 1) As an end - user, you can use these connectors on the disco.dev platform without any configuration; 2) As a developer, you can install the NPM package and use these pre - built connectors in your own MCP server. The project provides full TypeScript type support and a local development environment.

Applicable scenarios

Suitable for developers who need to connect AI assistants (such as Claude, Cursor, etc.) to enterprise SaaS tools, AI application developers who want to quickly build tool integration functions, and teams that need to centrally manage multiple tool API calls.

Main Features

Abundant pre - built connectors
Provides more than 35 production - ready SaaS tool connectors, including popular tools such as Asana, GitHub, Slack, Notion, Jira, Linear, Todoist, Google Drive, and Supabase.
Type - safe development experience
Built on TypeScript and Zod, it provides complete type definitions and validation to ensure type safety during development and runtime data validation.
Cross - platform runtime support
Supports running in various runtime environments such as Bun, Node.js, and Cloudflare Workers, providing flexible deployment options.
Friendly for local development
Provides an auto - reload function, supports rapid iterative development, and does not require complex server configuration.
Optimized for AI assistants
Specifically designed for AI coding assistants (such as Claude, Cursor, etc.), it provides clear type hints and configuration patterns to facilitate AI understanding and generation of correct code.
Zero - dependency server runtime
It does not depend on a specific server runtime or transport protocol, providing pure connector functions for easy integration into existing systems.
Advantages
Ready to use: Over 35 pre - built connectors, no need to develop from scratch
Type - safe: Full TypeScript type support, reducing runtime errors
Easy to integrate: Can be used with a simple NPM package installation
Cross - platform: Supports multiple JavaScript runtime environments
Community - driven: An open - source project with continuous updates and maintenance
AI - friendly: API design optimized specifically for AI assistants
Limitations
Requires basic programming knowledge: Although pre - built connectors are provided, certain development skills are still required for integration
Depends on external tools: Requires corresponding SaaS tool accounts and API credentials
Learning curve: Needs to understand the basic concepts of the MCP protocol
Customization limitations: Additional development may be required for highly customized integration requirements

How to Use

Environment Preparation
First, you need to install the Bun runtime environment, which is the recommended development environment for the project.
Clone the Project
Clone the project code to your local development environment.
Install Dependencies
Use Bun to install all the dependency packages required by the project.
Build the Project
Compile the TypeScript code to generate runnable JavaScript files.
Start the Test Server
Start a test connector server that does not require credentials to verify the successful installation.
Use Real Connectors
When using specific SaaS tool connectors, you need to provide the corresponding API credentials.

Usage Examples

AI Assistant Manages GitHub Tasks
Create, view, and update GitHub Issues directly through the Claude AI assistant without leaving the chat interface.
Intelligent Meeting Minutes Arrangement
Automatically organize Slack discussion content into Notion documents to form structured meeting minutes.
Cross - tool Task Synchronization
Tasks created in Asana are automatically synchronized to Linear and Todoist to keep task states consistent across multiple platforms.
Intelligent Document Retrieval
Retrieve relevant documents from Google Drive and Supabase databases to provide context information for AI.

Frequently Asked Questions

Do I need programming experience to use this project?
Is this project free?
Which SaaS tools are supported?
Can I use it in a production environment?
How to add a new connector?
Do I need to manage API credentials myself?
Which AI assistants are supported?
What about the performance?

Related Resources

Official Documentation
Detailed project documentation, including connector writing guides and local running instructions
disco.dev Platform
An online platform to use these connectors without configuration
GitHub Repository
Project source code and issue tracking
NPM Package - Connectors
Page of the @stackone/mcp - connectors NPM package
NPM Package - Configuration Types
Page of the @stackone/mcp - config - types NPM package
StackOne Official Website
Official website of the project development team
Model Context Protocol
Official documentation of the MCP protocol
Apache 2.0 License
Open - source license used by the project

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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