Build, validate, and deploy multi-agent AI solutions from any AI environment.
Most cloud and infrastructure work still happens through a UI a human drives. Ateam MCP server moves it into the conversation instead. Build, validate, and deploy multi-agent AI solutions from any AI environment.
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.
Because this one is hosted, setup is mostly authentication — you point your client at the endpoint and approve access. Nothing runs on your machine, so there is no runtime to keep patched.
The server publishes 13 tools. What each one is for:
adas_get_spec — Read the ADAS specification — skill schema, solution architecture, enums, agent guidesadas_get_examples — Get complete working examples — skills, connectors, solutionsadas_validate_skill — Validate a skill definition through the 5-stage pipelineadas_validate_solution — Validate a solution — cross-skill contracts + quality scoringadas_deploy_solution — Deploy a complete solution to productionadas_deploy_skill — Add a skill to an existing solutionadas_deploy_connector — Deploy a connector to ADAS Coreadas_list_solutions — List all deployed solutionsadas_get_solution — Inspect a solution — definition, skills, health, status, exportadas_update — Update a solution or skill incrementally (PATCH)adas_redeploy — Push changes live — regenerates MCP servers, deploys to ADAS Coreadas_solution_chat — Talk to the Solution Bot for guided modificationsConfiguration is passed through the environment: ADAS_TENANT, ADAS_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Plenty of cloud and infrastructure servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Ateam's toolset — adas_get_spec, adas_get_examples, adas_validate_skill and 10 more — is a fair guide to whether it matches your workflow. It is maintained by ariekogan; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| adas_get_spec | Read the ADAS specification — skill schema, solution architecture, enums, agent guides |
| adas_get_examples | Get complete working examples — skills, connectors, solutions |
| adas_validate_skill | Validate a skill definition through the 5-stage pipeline |
| adas_validate_solution | Validate a solution — cross-skill contracts + quality scoring |
| adas_deploy_solution | Deploy a complete solution to production |
| adas_deploy_skill | Add a skill to an existing solution |
| adas_deploy_connector | Deploy a connector to ADAS Core |
| adas_list_solutions | List all deployed solutions |
| adas_get_solution | Inspect a solution — definition, skills, health, status, export |
| adas_update | Update a solution or skill incrementally (PATCH) |
| adas_redeploy | Push changes live — regenerates MCP servers, deploys to ADAS Core |
| adas_solution_chat | Talk to the Solution Bot for guided modifications |
| Discovery | The Discovery tool exposed by this server. |
{
"mcpServers": {
"ateam": {
"command": "npx",
"args": ["-y", "@ateam-ai/mcp"],
"env": {
"ADAS_TENANT": "your-tenant",
"ADAS_API_KEY": "your-api-key"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| ADAS_TENANT | Configuration value read at startup. | Optional |
| ADAS_API_KEY | Credential the server authenticates with. | Yes |
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