Utilizes Node.js runtime for the server implementation, providing the foundation for the Agent Jobs MCP system.
Allows AI agents to create and manage jobs that execute on the Slack platform through the Agent Jobs system of the AI Connect platform.
Implements the server using TypeScript for type safety and better developer experience.
Enables AI agents to create and manage jobs that execute on WhatsApp through the Agent Jobs system of the AI Connect platform.
Uses Zod for schema validation within the MCP server implementation to ensure data integrity.
AI Connect MCP Server
An MCP (Model Context Protocol) server that allows AI agents to query and manage jobs in the AI Connect platform.
About AI Connect Jobs
AI Connect Jobs is a robust asynchronous task management system on the AI Connect platform, enabling the creation, monitoring, and execution of jobs across different platforms like Slack and WhatsApp, with support for scheduled execution, automatic retries, and timeout handling. The API provides endpoints to create, list, query, and cancel jobs, allowing developers and external systems to easily integrate asynchronous processing functionalities into their applications, automating complex workflows without the need to implement the entire task management infrastructure.
Features
This MCP Server provides tools for AI agents to:
- 📋 List Jobs: Query all jobs with advanced filtering
- 🔍 Get Specific Job: Retrieve details of a specific job by ID
- ✅ Create Jobs: Create new jobs for immediate or scheduled execution
- ❌ Cancel Jobs: Cancel running or scheduled jobs
- 📊 Monitor Status: Track job status (WAITING, RUNNING, COMPLETED, FAILED, CANCELED)
Technologies
- Node.js with TypeScript
- Model Context Protocol (MCP) by Anthropic
- Zod for schema validation
- AI Connect API for integration with the Agent Jobs system
Installation
NPX (Recommended)
You can run the MCP server directly using npx without installation:
Local Installation
- Clone the repository:
- Install dependencies:
- Configure environment variables (Optional):
The MCP server comes with default values from .env.example
, so you can run it without setting any environment variables. However, you must provide an API key for authentication.
Edit the .env
file with your credentials:
Important: If no environment variables are provided, the server will use these defaults:
DEFAULT_ORG_ID
:aiconnect
AICONNECT_API_URL
:https://api.aiconnect.cloud/api/v0
AICONNECT_API_KEY
: empty (must be provided for API calls to work)
- Build the project:
Usage
CLI Usage
The MCP server now supports CLI commands for easy management:
Setting Environment Variables:
Required Environment Variables:
AICONNECT_API_URL
: API endpoint URL (e.g., https://api.aiconnect.cloud/api/v0)AICONNECT_API_KEY
: Your API authentication key
CLI Command Examples:
Local Development
For local development, you can use npm scripts:
Configuration Options
This MCP server is designed to work out-of-the-box with minimal configuration. It uses a smart fallback system:
- With environment variables: Full control over all settings
- Without environment variables: Uses defaults from
.env.example
- Partial configuration: Mix of environment variables and defaults
Default Values (when no env vars are set):
DEFAULT_ORG_ID
:"aiconnect"
AICONNECT_API_URL
:"https://api.aiconnect.cloud/api/v0"
AICONNECT_API_KEY
:""
(empty - you must provide this)
Error Handling:
- The server will always start, even if environment variables are missing.
- If
AICONNECT_API_KEY
orAICONNECT_API_URL
are not provided, each tool will return a clear error message upon execution, guiding the user to configure the environment correctly. - If
DEFAULT_ORG_ID
is not set, it defaults to "aiconnect".
Running the MCP server
The server will start and wait for connections via stdio transport.
Claude Desktop Configuration
To use this MCP server with Claude Desktop, add the following configuration to your claude_desktop_config.json
file:
Available Tools
🔧 list_jobs
Lists all jobs with filtering and pagination options.
Parameters:
status
(optional): Filter by status (WAITING, RUNNING, COMPLETED, FAILED, CANCELED)job_type_id
(optional): Filter by job typechannel_code
(optional): Filter by channel codelimit
(optional): Result limit (default: 50)offset
(optional): Pagination offsetsort
(optional): Field and direction for sorting
🔍 get_job
Gets details of a specific job.
Parameters:
job_id
(required): ID of the job to query
✅ create_job
Creates a new job for execution.
Parameters:
target_channel
: Target channel configurationjob_type_id
: Job type IDconfig
: Job configuration (timeouts, retries, etc.)params
: Job-specific parametersscheduled_at
(optional): Date/time for scheduled executiondelay
(optional): Random delay in minutes
❌ cancel_job
Cancels a running or scheduled job.
Parameters:
job_id
(required): ID of the job to cancelreason
(optional): Cancellation reason
Job Status
Jobs can have the following status values:
WAITING
: Job waiting for executionSCHEDULED
: Job scheduled for future executionRUNNING
: Job currently runningCOMPLETED
: Job completed successfullyFAILED
: Job failedCANCELED
: Job was canceled
Usage Examples
List running jobs
Query specific job
Create scheduled job
Cancel job
Project Structure
Development
Available scripts
npm run build
: Compiles TypeScriptnpm start
: Runs the compiled server
Adding new tools
Adding a new tool is simple:
- Create a new TypeScript file inside the
src/tools/
directory (e.g.,my_new_tool.ts
). - Implement your tool logic following the existing pattern. The server will automatically detect and register it on startup.
- Recompile the project with
npm run build
.
Contributing
- Fork the project
- Create a feature branch (
git checkout -b feature/new-feature
) - Commit your changes (
git commit -am 'Add new feature'
) - Push to the branch (
git push origin feature/new-feature
) - Open a Pull Request
License
This project is licensed under the MIT License.
Support
For technical support or questions about AI Connect Jobs:
- Check the API documentation
- Contact the AI Connect development team
Note: This project was developed using the Anthropic mcp-tools scaffold for integration with the AI Connect platform.
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Allows AI agents to query and manage asynchronous jobs in the Agent Jobs system of the AI Connect platform, supporting operations like listing, creating, and canceling jobs.
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