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:

npx @aiconnect/agentjobs-mcp --help

Local Installation

Clone the repository:

git clone <repository-url>
cd agentjobs-mcp

Install dependencies:

npm install

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.

cp .env.example .env

Edit the .env file with your credentials:

DEFAULT_ORG_ID=your-organization     # Default: aiconnect
AICONNECT_API_KEY=your-api-key       # Required: Must be provided
AICONNECT_API_URL=https://api.aiconnect.cloud/api/v0  # Default

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:

npm run build

Usage

CLI Usage

The MCP server now supports CLI commands for easy management:

# Show help and usage information
npx @aiconnect/agentjobs-mcp --help

# Show version information
npx @aiconnect/agentjobs-mcp --version

# Show current configuration status
npx @aiconnect/agentjobs-mcp --config

# Start MCP server (default behavior)
npx @aiconnect/agentjobs-mcp

Setting Environment Variables:

# Using environment variables with npx
AICONNECT_API_URL=https://api.aiconnect.cloud/api/v0 \
AICONNECT_API_KEY=your-api-key-here \
npx @aiconnect/agentjobs-mcp

# Or create a .env file (recommended for development)
cp .env.example .env
# Edit .env with your credentials
npx @aiconnect/agentjobs-mcp

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:

# Quick help
npx @aiconnect/agentjobs-mcp -h

# Check version
npx @aiconnect/agentjobs-mcp -v

# Verify configuration before starting
npx @aiconnect/agentjobs-mcp -c

# Test with environment variables
env AICONNECT_API_URL=https://api.aiconnect.cloud/api/v0 \
    AICONNECT_API_KEY=test-key \
    npx @aiconnect/agentjobs-mcp --config

Local Development

For local development, you can use npm scripts:

# Build and test CLI commands
npm run cli:help
npm run cli:version  
npm run cli:config

# Run test suite (if available)
npm run test:cli

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 or AICONNECT_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

npm start

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:

{
  "mcpServers": {
    "agentjobs": {
      "command": "node",
      "args": ["/path/to/agentjobs-mcp/build/index.js"],
      "env": {
        "DEFAULT_ORG_ID": "your-organization",
        "AICONNECT_API_KEY": "your-api-key",
        "AICONNECT_API_URL": "https://api.aiconnect.cloud/api/v0"
      }
    }
  }
}

Local Development with Claude Code

For development and testing, you can add this MCP server directly to your Claude Code project:

# Prerequisites: build the project first
npm install
npm run build

# Configure your .env file
cp .env.example .env
# Edit .env with your API credentials

# Add MCP server to Claude Code (project scope)
claude mcp add --scope project agentjobs -- ./mcp-agentjobs.sh

This allows you to test and use the AgentJobs tools directly within Claude Code during development, providing immediate feedback and easier debugging.

Available Tools

📊 `get_jobs_stats`

Get aggregated statistics for agent jobs without retrieving individual job data. Optimized for dashboards and monitoring with minimal network overhead.

Parameters:

scheduled_at_gte: Start of period (ISO 8601)
scheduled_at_lte: End of period (ISO 8601)
org_id: Organization filter
job_type_id: Job type filter
tags: Tags filter (comma-separated)
status: Status filter
channel_code: Channel filter

🔧 `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 type
channel_code (optional): Filter by channel code
limit (optional): Result limit (default: 50)
offset (optional): Pagination offset
sort (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 configuration
job_type_id: Job type ID
config: Job configuration (timeouts, retries, etc.)
params: Job-specific parameters
scheduled_at (optional): Date/time for scheduled execution
delay (optional): Random delay in minutes

❌ `cancel_job`

Cancels a running or scheduled job.

Parameters:

job_id (required): ID of the job to cancel
reason (optional): Cancellation reason

Job Status

Jobs can have the following status values:

WAITING: Job waiting for execution
SCHEDULED: Job scheduled for future execution
RUNNING: Job currently running
COMPLETED: Job completed successfully
FAILED: Job failed
CANCELED: Job was canceled

Usage Examples

List running jobs

Agent: "Show me all jobs that are currently running"

Query specific job

Agent: "What's the status of job job-123?"

Create scheduled job

Agent: "Create a daily report job for Slack channel C123456 to run tomorrow at 9 AM"

Cancel job

Agent: "Cancel job job-456 because it's no longer needed"

Project Structure

agentjobs-mcp/
├── src/                    # TypeScript source code
│   ├── index.ts           # Main MCP server entry point
│   ├── config.ts          # Configuration loader
│   └── tools/             # Directory for all MCP tools
│       ├── get_jobs_stats.ts # Tool for getting job statistics
│       ├── list_jobs.ts   # Tool for listing jobs
│       ├── get_job.ts     # Tool for getting a job
│       ├── create_job.ts  # Tool for creating a job
│       └── cancel_job.ts  # Tool for canceling a job
├── build/                 # Compiled JavaScript code
├── docs/                  # Documentation
│   └── agent-jobs-api.md  # API documentation
├── package.json           # Dependencies and scripts
├── tsconfig.json          # TypeScript configuration
├── .env.example           # Environment variables example
└── README.md              # This file

Development

Available scripts

npm run build: Compiles TypeScript
npm start: Runs the compiled server
npm run debug: Runs server in debug mode with detailed logging
npm run test:tools: Tests tool loading without starting server
npm run cli:config: Shows current configuration
npm run cli:version: Shows version information
npm run cli:help: Shows help information

Debugging

For detailed debugging information, see Debug Guide.

Quick Debug Commands:

# Test configuration
npm run cli:config

# Test tool loading
npm run test:tools

# Run in debug mode
MCP_DEBUG=true npm run debug

# Use debug helper script (Fish shell)
./debug.fish help
./debug.fish quick

Debug Environment:

# Copy debug environment template
cp .env.debug .env
# Edit .env with your API credentials
# Run with debug environment
./debug.fish debug-with-env

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.
Test with npm run test:tools to verify loading.

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.

Agent Jobs MCP Server

README Documentation

AI Connect MCP Server

About AI Connect Jobs

Features

Technologies

Installation

NPX (Recommended)

Local Installation

Usage

CLI Usage

Local Development

Configuration Options

Running the MCP server

Claude Desktop Configuration

Local Development with Claude Code

Available Tools

📊 `get_jobs_stats`

🔧 `list_jobs`

🔍 `get_job`

✅ `create_job`

❌ `cancel_job`

Job Status

Usage Examples

List running jobs

Query specific job

Create scheduled job

Cancel job

Project Structure

Development

Available scripts

Debugging

Adding new tools

Contributing

License

Support

Quick Install

Quick Actions

Key Features

Agent Jobs MCP Server

README Documentation

AI Connect MCP Server

About AI Connect Jobs

Features

Technologies

Installation

NPX (Recommended)

Local Installation

Usage

CLI Usage

Local Development

Configuration Options

Running the MCP server

Claude Desktop Configuration

Local Development with Claude Code

Available Tools

📊 get_jobs_stats

🔧 list_jobs

🔍 get_job

✅ create_job

❌ cancel_job

Job Status

Usage Examples

List running jobs

Query specific job

Create scheduled job

Cancel job

Project Structure

Development

Available scripts

Debugging

Adding new tools

Contributing

License

Support

Quick Install

Quick Actions

Key Features

📊 `get_jobs_stats`

🔧 `list_jobs`

🔍 `get_job`

✅ `create_job`

❌ `cancel_job`