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mcp-server

Streamline AI with mission-control

Dispatch tasks and govern AI operations from one dashboard, for founders using AI agents, with 5.1k+ GitHub stars
intermediateโฑ 1-2 hours๐Ÿ’ต Free self-hosted
5,753 stars963 forksTypeScriptUpdated 7/15/2026100% free ยท open source
What it is

Manage and govern your AI agents from a central dashboard.

What you can make with it

Automations like: automate data transfer between Amazon S3 and Google Sheets, or send custom emails using Amazon SES when a customer places an order on your e-commerce site.

How it helps

It helps you streamline your AI operations and save time by avoiding the need to manually switch between different AI tools.

Real use case example

"A founder like you can use this to automate data import from Amazon to Notion by setting up an AI agent in this mission control dashboard, then create a trigger for new products, and finally have the data synced within a few minutes."

If you're new

Choose this when you're new to AI automation and want to get started with building simple automations.

If you're senior

A senior engineer/professional would likely use this for complex AI orchestration or when they need more control over their AI operations.

Common confusion cleared up

Some first-time users might confuse this with other self-hosted AI orchestration platforms, but this specific one emphasizes mission control capabilities.

Best inside these AI tools
Claude DesktopCursorCodex CLI
Pairs with
Claude APIStripe webhook
Why we list it on WorkflowStacks: This platform is available here because it's a widely-used and reliable option for managing AI operations, especially for founders.
What it does

Mission-control is a platform that helps you manage and orchestrate multiple AI agents, workflows, and operations from a single dashboard.

When to use it
  • โ€ขYou have multiple AI models or agents that need to work together to accomplish a task
  • โ€ขYou want to monitor and control the cost of running AI workflows and operations
  • โ€ขYou need to manage complex AI workflows and want a centralized platform to do so
Quick start
  1. 1Install and set up the mission-control platform on your server or local machine
  2. 2Configure and connect your AI agents and workflows to the platform
  3. 3Define and create workflows that dispatch tasks to your AI agents
  4. 4Monitor and govern your AI operations from the mission control dashboard
Ready-to-paste prompt
dispatch task 'sentiment-analysis' to agent ' transformer-model' with input '{"text": "This is a sample text"}'
Saves to your device

Topics

agent-orchestration
ai-agents
ai-automation
ai-dashboard
claude
dashboard
developer-tools
llm
mcp
nextjs
open-source
openclaw
self-hosted
sqlite
task-management
typescript
What's inside โ€” free to inspect
No purchase needed

Read the entire source before you build โ€” unlike paid marketplaces that hide it behind a buy button.

36
top-level files
11
folders
21.1M
repo size
MIT
license
Key files
eslint.config.mjs
next.config.js
package.json
playwright.config.ts
playwright.openclaw.gateway.config.ts
playwright.openclaw.local.config.ts
File tree
.github/
docs/
examples/
messages/
ops/
public/
scripts/
skills/
src/
tests/
wiki/
.dockerignore
.env.example
.env.test
.gitignore
.node-version
.npmrc
.nvmrc
CHANGELOG.md
CLAUDE.md
CODE_OF_CONDUCT.md
CONTRIBUTING.md
docker-compose.hardened.yml
docker-compose.yml
Quick Actions
Details
Creator
builderz-labs
Language
TypeScript
Category
mcp-server
Published
2/13/2026

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