Ateam Mcp

ariekogan/ateam-mcp

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.

tools: 12
transport: STDIO, HTTP
last updated: Feb 17, 2026

View on GitHub

Tools

12 tools

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

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 ex...one 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

connectorsarray

Array of connector metadata (id, name, transport, command, args)

mcp_storeobject

Optional: connector source code files. Key = connector id, value = array of {path, content}

skillsarray

Array of full skill definitions

solutionobject

Solution architecture — identity, grants, handoffs, routing

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

skill_idstring

Optional: read a specific skill by ID (original or internal)

solution_idstring

The solution ID

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 st...one of definition · skills · health · status · export · validate

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

skill_idstring

Required when target is 'skill'

solution_idstring

The solution ID

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

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

Readme

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"

View the full README on GitHub

Details

Repository: github.com/ariekogan/ateam-mcp
Category: AI & LLM Tools
Package: @ateam-ai/mcp
Transport: STDIO, HTTP
Registry: MCP registry, active

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