Usage — Agent / MCP / CLI¶
genius-agent exposes its capability three ways: as an integrated agent you drive
over ACP / the Web UI, as an MCP tool surface an orchestrator composes, and as a
CLI you launch directly. The full capability set and enterprise-readiness matrix
are in Overview.
As an MCP server¶
genius-agent composes the tools of the MCP servers declared in its
mcp_config.json (or reached via MCP_URL) into a single orchestration plane, and
exposes its graph-flow capability over MCP. Reads work with no configuration beyond a
model provider key; authorization is enforced through Eunomia when
EUNOMIA_TYPE=embedded or remote.
| Capability | Description |
|---|---|
run_graph_flow |
Execute a multi-step workflow through the agent's Pydantic-Graph orchestration engine (declared in a2a.json). |
| Composed MCP tools | Every tool registered by the MCP servers in mcp_config.json becomes callable through the agent. |
Example prompts that drive the agent:
- "Run the deployment workflow against the staging environment." →
run_graph_flow - "Search the catalog and summarize the top results." → a composed MCP tool call
- "Plan a multi-step task and execute each step." → graph orchestration
As a Python API¶
The agent server is launched programmatically through the package entry point. The
agent_server() function builds and runs the integrated agent from the environment:
from genius_agent.agent_server import agent_server
# Builds the Pydantic-AI graph agent from API_KEY / MODEL_NAME / DEFAULT_SYSTEM_PROMPT
# and the MCP tool surface, then serves ACP + the Agent Web UI.
agent_server()
Under the hood it composes the agent-utilities building blocks
(create_agent_server, build_system_prompt_from_workspace, load_identity,
initialize_workspace), so the agent identity, system prompt, and workspace are
resolved from the environment and the bundled agent_data/ workspace.
As a CLI¶
The genius-agent console script is the primary entry point. Provide a model
provider and identity, then run:
export API_KEY=your_model_provider_key
export MODEL_NAME=openai/gpt-4o
export DEFAULT_SYSTEM_PROMPT="You are Genius Agent, an orchestration specialist."
# Interactive terminal agent
genius-agent --provider openai --model-id gpt-4o
# Networked agent server with the Web UI + ACP
genius-agent --provider openai --model-id gpt-4o --host 0.0.0.0 --port 9000 --web
Connect the agent to a remote MCP tool surface:
Inspect every available flag:
Each optional capability reads its own credentials and remains inactive when those
credentials are absent. The full environment set is documented in
.env.example.