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Ateam Mcp

ariekogan/ateam-mcp
12 toolsSTDIO, HTTPregistry active
Summary

Bridges Claude, ChatGPT, Cursor, and other AI assistants directly to the ADAS multi-agent platform. Exposes twelve tools that let your AI read the ADAS spec, validate skill and solution definitions through a five-stage pipeline, deploy to production, and monitor health. The workflow is conversational: describe a customer support system with escalation, and the assistant builds the skill definitions, validates them, deploys, and confirms everything is running. No manual JSON authoring or dashboard hopping. Works over stdio for local setups or streamable HTTP at mcp.ateam-ai.com for remote access. Particularly useful if you're building production agent systems on ADAS and want to stay in your editor or chat interface instead of context switching to docs and deployment tools.

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Tools

Public tool metadata for what this MCP can expose to an agent.

12 tools
adas_get_specGet the ADAS specification — schemas, validation rules, system tools, agent guides, and templates. Use this to understand how to build skills and solutions.1 params

Get the ADAS specification — schemas, validation rules, system tools, agent guides, and templates. Use this to understand how to build skills and solutions.

Parameters* required
topicstring
What to fetch: 'overview' = API overview + endpoints, 'skill' = full skill spec, 'solution' = full solution spec, 'enums' = all enum valuesone of overview · skill · solution · enums
adas_get_examplesGet complete working examples that pass validation. Study these before building your own.1 params

Get complete working examples that pass validation. Study these before building your own.

Parameters* required
typestring
Example type: 'skill' = Order Support Agent, 'connector' = stdio MCP connector, 'connector-ui' = UI-capable connector, 'solution' = full 3-skill e-commerce solution, 'index' = list all available examplesone of skill · connector · connector-ui · solution · index
adas_validate_skillValidate a skill definition through the 5-stage ADAS validation pipeline. Returns errors and suggestions to fix.1 params

Validate a skill definition through the 5-stage ADAS validation pipeline. Returns errors and suggestions to fix.

Parameters* required
skillobject
The full skill definition object to validate
adas_validate_solutionValidate a solution definition — cross-skill contracts, grant economy, handoffs, and LLM quality scoring.2 params

Validate a solution definition — cross-skill contracts, grant economy, handoffs, and LLM quality scoring.

Parameters* required
skillsarray
Array of skill definitions included in the solution
solutionobject
The full solution definition object to validate
adas_deploy_solutionDeploy a complete solution to ADAS Core — identity, connectors, skills. The Skill Builder auto-generates MCP servers from tool definitions. This is the main deployment action.4 params

Deploy a complete solution to ADAS Core — identity, connectors, skills. The Skill Builder auto-generates MCP servers from tool definitions. This is the main deployment action.

Parameters* required
skillsarray
Array of full skill definitions
solutionobject
Solution architecture — identity, grants, handoffs, routing
mcp_storeobject
Optional: connector source code files. Key = connector id, value = array of {path, content}
connectorsarray
Array of connector metadata (id, name, transport, command, args)
adas_deploy_skillDeploy a single skill into an existing solution.2 params

Deploy a single skill into an existing solution.

Parameters* required
skillobject
Full skill definition
solution_idstring
The existing solution ID to add the skill to
adas_deploy_connectorDeploy a connector — registers in the Skill Builder catalog and connects in ADAS Core.1 params

Deploy a connector — registers in the Skill Builder catalog and connects in ADAS Core.

Parameters* required
connectorobject
Connector metadata (id, name, transport, command, args)
adas_list_solutionsList all solutions deployed in the Skill Builder.

List all solutions deployed in the Skill Builder.

No parameter schema in public metadata yet.

adas_get_solutionRead solution state — definition, skills, health, status, or export. Use this to inspect deployed solutions.3 params

Read solution state — definition, skills, health, status, or export. Use this to inspect deployed solutions.

Parameters* required
viewstring
What to read: 'definition' = full solution def, 'skills' = list skills, 'health' = live health check, 'status' = deploy status, 'export' = exportable bundle, 'validate' = re-validate from stored state, 'connectors_health' = connector statusone of definition · skills · health · status · export · validate
skill_idstring
Optional: read a specific skill by ID (original or internal)
solution_idstring
The solution ID
adas_updateUpdate a deployed solution or skill incrementally using PATCH. Supports dot notation for scalar fields and _push/_delete/_update for arrays.4 params

Update a deployed solution or skill incrementally using PATCH. Supports dot notation for scalar fields and _push/_delete/_update for arrays.

Parameters* required
targetstring
What to update: 'solution' or 'skill'one of solution · skill
updatesobject
The update payload — use dot notation for scalars (e.g. 'problem.statement'), and tools_push/tools_delete/tools_update for array operations
skill_idstring
Required when target is 'skill'
solution_idstring
The solution ID
adas_redeployRe-deploy after making updates. Regenerates MCP servers and pushes to ADAS Core.2 params

Re-deploy after making updates. Regenerates MCP servers and pushes to ADAS Core.

Parameters* required
skill_idstring
Optional: redeploy a single skill. Omit to redeploy all skills.
solution_idstring
The solution ID
adas_solution_chatSend a message to the Solution Bot — an AI assistant that understands your deployed solution and can help with modifications.2 params

Send a message to the Solution Bot — an AI assistant that understands your deployed solution and can help with modifications.

Parameters* required
messagestring
Your message to the Solution Bot
solution_idstring
The solution ID

ateam-mcp

Give any AI the ability to build, validate, and deploy production multi-agent systems.

This is an MCP server that connects AI assistants — ChatGPT, Claude, Gemini, Copilot, Cursor, Windsurf, and any MCP-compatible environment — directly to the ADAS platform.

An AI developer says "Build me a customer support system with order tracking and escalation" — and their AI assistant handles the entire lifecycle: reads the spec, builds skill definitions, validates them, deploys to production, and verifies health. No manual JSON authoring, no docs reading, no copy-paste workflows.

Why this matters

Today, building multi-agent systems requires deep platform knowledge, manual configuration, and switching between docs, editors, and dashboards. ateam-mcp eliminates all of that by making the ADAS platform a native capability of the AI tools developers already use.

The AI assistant becomes the developer interface:

Developer: "Create an identity verification agent that checks documents,
            validates faces, and escalates fraud cases"

AI Assistant:
  → reads ADAS spec (adas_get_spec)
  → studies working examples (adas_get_examples)
  → builds skill + solution definitions
  → validates iteratively (adas_validate_skill, adas_validate_solution)
  → deploys to production (adas_deploy_solution)
  → verifies everything is running (adas_get_solution → health)

Developer: "Add a new skill that handles address verification"

AI Assistant:
  → deploys into the existing solution (adas_deploy_skill)
  → redeploys (adas_redeploy)
  → confirms health

No context switching. No manual steps. The full ADAS platform — specs, validation, deployment, monitoring — is available as natural language.

How it reaches the AI community

ChatGPT users

ChatGPT supports MCP connectors in Developer Mode. Users connect by pasting a single URL:

Settings → Connectors → Developer Mode → paste https://mcp.ateam-ai.com

That's it. All 12 ADAS tools appear in ChatGPT. Any ChatGPT Pro, Plus, Business, or Enterprise user can build and deploy multi-agent solutions through conversation.

Claude users

Claude Desktop — install as an extension (one-click) or add to config:

{
  "mcpServers": {
    "ateam": {
      "command": "npx",
      "args": ["-y", "@ateam-ai/mcp"],
      "env": {
        "ADAS_TENANT": "your-tenant",
        "ADAS_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code — one command:

claude mcp add ateam -- npx -y @ateam-ai/mcp

Cursor / Windsurf / VS Code (Copilot)

Add to .cursor/mcp.json, mcp_config.json, or .vscode/mcp.json:

{
  "mcpServers": {
    "ateam": {
      "command": "npx",
      "args": ["-y", "@ateam-ai/mcp"],
      "env": {
        "ADAS_TENANT": "your-tenant",
        "ADAS_API_KEY": "your-api-key"
      }
    }
  }
}

Gemini and other platforms

As MCP adoption grows (it's now governed by the Agentic AI Foundation under the Linux Foundation, co-founded by Anthropic, OpenAI, and Block), every AI platform that implements MCP gets access to ateam-mcp automatically. The remote HTTP endpoint (https://mcp.ateam-ai.com) works with any client that supports Streamable HTTP transport.

Discovery

Developers find ateam-mcp through:

  • npm — npm search mcp ai-agents → @ateam-ai/mcp
  • Official MCP Registry — registry.modelcontextprotocol.io
  • Claude Desktop Extensions — built-in extension browser
  • Claude Code Plugin Marketplace — /plugin → Discover tab
  • Windsurf MCP Marketplace — built-in marketplace
  • VS Code MCP Gallery — Extensions view
  • Community directories — Smithery, mcp.so, PulseMCP (30,000+ combined listings)

Available tools

ToolWhat it does
adas_get_specRead the ADAS specification — skill schema, solution architecture, enums, agent guides
adas_get_examplesGet complete working examples — skills, connectors, solutions
adas_validate_skillValidate a skill definition through the 5-stage pipeline
adas_validate_solutionValidate a solution — cross-skill contracts + quality scoring
adas_deploy_solutionDeploy a complete solution to production
adas_deploy_skillAdd a skill to an existing solution
adas_deploy_connectorDeploy a connector to ADAS Core
adas_list_solutionsList all deployed solutions
adas_get_solutionInspect a solution — definition, skills, health, status, export
adas_updateUpdate a solution or skill incrementally (PATCH)
adas_redeployPush changes live — regenerates MCP servers, deploys to ADAS Core
adas_solution_chatTalk to the Solution Bot for guided modifications

Setup

# Clone
git clone https://github.com/ariekogan/ateam-mcp.git
cd ateam-mcp

# Install
npm install

# Configure
cp .env.example .env
# Edit .env with your ADAS tenant and API key

# Run
npm start

Architecture

┌─────────────────────────────────────────────┐
│  AI Environment                             │
│  (ChatGPT / Claude / Cursor / Windsurf)     │
│                                             │
│  Developer: "build me a support system"     │
└──────────────────┬──────────────────────────┘
                   │ MCP protocol
                   │ (stdio or HTTP)
┌──────────────────▼──────────────────────────┐
│  ateam-mcp                                  │
│  12 tools — spec, validate, deploy, manage  │
└──────────────────┬──────────────────────────┘
                   │ HTTPS
                   │ X-ADAS-TENANT / X-API-KEY
┌──────────────────▼──────────────────────────┐
│  ADAS External Agent API                    │
│  api.ateam-ai.com                           │
└──────────────────┬──────────────────────────┘
                   │
┌──────────────────▼──────────────────────────┐
│  ADAS Core                                  │
│  Multi-agent runtime                        │
└─────────────────────────────────────────────┘

License

MIT

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Categories
AI & LLM Tools
Registryactive
Package@ateam-ai/mcp
TransportSTDIO, HTTP
UpdatedFeb 17, 2026
View on GitHub

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