agent-team-lab
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_MODEL | No | The OpenAI model identifier to use with the 'openai' provider. Defaults to the provider's built-in default if not set. | |
| OPENAI_API_KEY | No | Your OpenAI API key. Required when using the 'openai' provider. | |
| AGENT_TEAM_PROVIDER | No | The provider adapter to use: openai, openai-compatible, hermes, or mock. | openai |
| AGENT_TEAM_ALLOWED_ROOT | No | Absolute path to the allowed root directory for project analysis. The server will only read files within this root. | |
| OPENAI_COMPATIBLE_MODEL | No | Model name for the OpenAI-compatible API. Required when using the 'openai-compatible' provider. | |
| OPENAI_COMPATIBLE_API_KEY | No | API key for the OpenAI-compatible API. Required when using the 'openai-compatible' provider. | |
| OPENAI_COMPATIBLE_BASE_URL | No | Base URL for an OpenAI-compatible API (e.g. Ollama, vLLM, LocalAI). Required when using the 'openai-compatible' provider. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_expertsA | List the expert roles available in this agent team. |
| ask_expertC | Ask one specialist to review a task and the readable source files in a project. |
| run_teamC | Run the connected PM, architecture, programming, QA and security workflow. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clear, distinct purpose: listing expert roles, consulting a single expert, and running the full team workflow. There is no ambiguity or overlap between them.
All tool names follow a consistent verb_noun pattern using snake_case: list_experts, ask_expert, run_team. The naming is uniform and predictable.
Three tools is a well-scoped set for an agent team lab. Each tool addresses a core interaction—discover, consult, execute—without unnecessary bloat.
The core workflows are covered: listing experts, asking one expert, and running the full team. Minor gaps exist such as no explicit status/result polling or workflow cancellation, but the surface is reasonably complete for its scope.