genius-agent 3.0.0

GeniusAgent Search Engine for Agentic AI!

Genius Agent

CLI or API | Agent

Version: 3.0.0

Documentation — Installation, deployment, usage across the agent, MCP, and CLI interfaces are maintained in the official documentation.

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Overview

Genius Agent is a production-grade Agent and Model Context Protocol (MCP) server designed to interface directly with GeniusAgent Search Engine for Agentic AI!.

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Key Features

• Enterprise-Grade Security: Comprehensive support for Eunomia policies, OIDC token delegation, and granular execution context tracking.
• Integrated Graph Agent: Built-in Pydantic AI agent supporting the Agent Control Protocol (ACP) and standard Web interfaces (AG-UI).
• Native Telemetry & Tracing: Out-of-the-box OpenTelemetry exports and native Langfuse tracing.

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CLI or API

This agent wraps the GeniusAgent Search Engine for Agentic AI! API. You can interact with it programmatically or via its integrated execution entrypoints.

Detailed instructions on how to use the underlying API wrappers, extended schema bindings, and developer SDK references are maintained in docs/index.md.

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Agent

This repository features a fully integrated Pydantic AI Graph Agent. It communicates over the Agent Control Protocol (ACP) and interacts seamlessly with the Agent Web UI (AG-UI) and Terminal interface.

Running the Agent CLI

To start the interactive command-line agent:

# Optional: override the agent's identity / workspace
export DEFAULT_AGENT_NAME="Genius Agent"
export WORKSPACE_DIR="/path/to/workspace"

# Run the agent server (provider / model / key are CLI args)
genius-agent --provider openai --model-id gpt-4o

Docker Compose Orchestration

The following docker/agent.compose.yml configures the Agent, Web UI, and Terminal Interface together:

version: '3.8'

services:
  genius-agent-agent:
    image: knucklessg1/genius-agent:latest
    container_name: genius-agent-agent
    hostname: genius-agent-agent
    restart: always
    env_file:
      - ../.env
    command: [ "genius-agent" ]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9000
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
      - ENABLE_OTEL=True
    ports:
      - "9000:9000"
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:9000/health')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    logging:
      driver: json-file
      options:
        max-size: "10m"
        max-file: "3"

Detailed graph node architecture explanations, custom skill configurations, and agentic trace guides are available in docs/agent.md.

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Security & Governance

Built directly upon the enterprise-ready agent-utilities core, standard security parameters are fully supported:

Access Control & Policy Enforcement

• Eunomia Policies: Fine-grained, policy-driven tool authorization. Supports none, local embedded (mcp_policies.json), or centralized remote modes.
• OIDC Token Delegation: Compliant with RFC 8693 token exchange for flowing authenticating user credentials from Web UI / ACP → Agent → MCP.
• Scoped Credentials: Execution context runs restricted to the specific caller identity.

Runtime Security Grid

Feature	Functionality	Enablement
Tool Guard	Sensitivity inspection with human-in-the-loop validation	Enabled by default
Prompt Injection Defense	Input scanning, repetition monitoring, and recursive loop blocks	Enabled by default
Context Safety Guard	Stuck-loop detectors and contextual overflow preemptive alerts	Enabled by default

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Installation

Pick the extra that matches what you want to run:

Extra	Installs	Use when
genius-agent[mcp]	Slim MCP/runtime base only (agent-utilities[mcp] — FastMCP/FastAPI)	You only need the lightweight tool-hosting base (smallest install)
genius-agent[agent]	Full agent runtime (agent-utilities[agent,logfire] — Pydantic AI + the epistemic-graph engine)	You run the integrated agent (the primary surface)
genius-agent[all]	Everything (mcp + agent + logfire)	Development / both surfaces

# Slim base (smallest install)
uv pip install "genius-agent[mcp]"

# Full agent runtime (Pydantic AI + epistemic-graph engine) — recommended
uv pip install "genius-agent[agent]"

# Everything (development)
uv pip install "genius-agent[all]"      # or: python -m pip install "genius-agent[all]"

Knowledge-graph database (epistemic-graph)

The full agent ([agent]) embeds the epistemic-graph engine (pulled in transitively via agent-utilities[agent]). For production — or to share one knowledge graph across multiple agents — run epistemic-graph as its own database container and point the agent at it instead of embedding it. Deployment recipes (single-node + Raft HA), connection config, and the full database architecture (with diagrams) are documented in the epistemic-graph deployment guide. The slim [mcp] base does not require the database.

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Environment Variables

Package environment variables

Variable	Example	Description
ENABLE_OTEL	True
OTEL_EXPORTER_OTLP_ENDPOINT	http://localhost:8080/api/public/otel
OTEL_EXPORTER_OTLP_PUBLIC_KEY	pk-...
OTEL_EXPORTER_OTLP_SECRET_KEY	sk-...
OTEL_EXPORTER_OTLP_PROTOCOL	http/protobuf
OTEL_EXPORTER_OTLP_HEADERS	—	OTLP auth header, e.g. "Authorization=Basic "
EUNOMIA_TYPE	none	options: none, embedded, remote
EUNOMIA_POLICY_FILE	mcp_policies.json
EUNOMIA_REMOTE_URL	http://eunomia-server:8000
WORKSPACE_DIR	/home/apps/workspace/agent-packages	workspace root the agent initializes from
MCP_CONFIG	mcp_config.json	path to the MCP config the agent loads
GRAPH_DB_PATH	—	path to the local graph DB backing store
GRAPHDB_PASSWORD	letmein	password for the FalkorDB / graph DB backend
AGENT_UTILITIES_TESTING	true	set "true" to skip live integration tests

Inherited agent-utilities variables (apply to every connector)

Variable	Example	Description
TRANSPORT	stdio	MCP transport: stdio
HOST	0.0.0.0	Bind host (HTTP transports)
PORT	8000	Bind port (HTTP transports)
MCP_TOOL_MODE	condensed	Tool surface: condensed
MCP_ENABLED_TOOLS	—	Comma-separated tool allow-list
MCP_DISABLED_TOOLS	—	Comma-separated tool deny-list
MCP_ENABLED_TAGS	—	Comma-separated tag allow-list
MCP_DISABLED_TAGS	—	Comma-separated tag deny-list
MCP_CLIENT_AUTH	—	Outbound MCP auth (oidc-client-credentials for fleet calls)
OIDC_CLIENT_ID	—	OIDC client id (service-account auth)
OIDC_CLIENT_SECRET	—	OIDC client secret (service-account auth)
DEBUG	False	Verbose logging
PYTHONUNBUFFERED	1	Unbuffered stdout (recommended in containers)
MCP_URL	http://localhost:8000/mcp	URL of the MCP server the agent connects to
PROVIDER	openai	LLM provider for the agent
MODEL_ID	gpt-4o	Model id for the agent
ENABLE_WEB_UI	True	Serve the AG-UI web interface

14 package + 17 inherited variable(s). Auto-generated from .env.example + the shared agent-utilities set — do not edit.

Every variable the agent reads, grouped by purpose.

Agent runtime

Variable	Description	Default
DEFAULT_AGENT_NAME	Override the agent's identity name	Genius Agent
AGENT_DESCRIPTION	Override the agent description	identity / built-in
AGENT_SYSTEM_PROMPT	Override the agent system prompt	identity / workspace-derived
WORKSPACE_DIR	Agent workspace directory	—
MCP_URL	URL of the MCP server the agent connects to	http://localhost:8000/mcp
MCP_CONFIG	Path to an mcp_config.json for downstream tool servers	mcp_config.json
PROVIDER	LLM provider (e.g. openai)	openai
MODEL_ID	Model id (e.g. gpt-4o)	gpt-4o
LLM_API_KEY	LLM provider API key	—
ENABLE_WEB_UI	Serve the AG-UI web interface	True
GRAPH_DB_PATH	Path to the local epistemic-graph database file	—
GRAPHDB_PASSWORD	Password for an external graph database	—
HOST	Bind host	0.0.0.0
PORT	Bind port	9000
DEBUG	Verbose logging	False
PYTHONUNBUFFERED	Unbuffered stdout (recommended in containers)	1

Telemetry & governance

Variable	Description	Default
ENABLE_OTEL	Enable OpenTelemetry export	True
OTEL_EXPORTER_OTLP_ENDPOINT	OTLP collector endpoint	—
OTEL_EXPORTER_OTLP_HEADERS	OTLP exporter headers	—
OTEL_EXPORTER_OTLP_PUBLIC_KEY / OTEL_EXPORTER_OTLP_SECRET_KEY	OTLP auth keys	—
OTEL_EXPORTER_OTLP_PROTOCOL	OTLP protocol (e.g. http/protobuf)	—
EUNOMIA_TYPE	Authorization mode: none, embedded, remote	none
EUNOMIA_POLICY_FILE	Embedded policy file	mcp_policies.json
EUNOMIA_REMOTE_URL	Remote Eunomia server URL	—

See .env.example for a copy-paste starting point.

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Documentation

The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.

Page	Contents
Installation	pip, source, extras, prebuilt Docker image
Deployment	run the agent server, Compose, Caddy + Technitium, env config
Usage	the agent, the MCP tool surface, the CLI
Overview	capabilities, enterprise readiness, configuration
Concepts	concept registry (CONCEPT:GENIUS-*)

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Repository Owners

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Contribute

Contributions are welcome! Please ensure code quality by executing local checks before submitting pull requests:

• Format code using ruff format .
• Lint code using ruff check .
• Validate type-safety with mypy .
• Execute test suites using pytest

Deploy with agent-os-genesis

This package can be provisioned for you — skill-guided — by the agent-os-genesis universal skill (its single-package deploy mode): it picks your install method, seeds secrets to OpenBao/Vault (or .env), trusts your enterprise CA, registers the MCP server, and verifies it — the same machinery that stands up the whole Agent OS, narrowed to just this package. Ask your agent to "deploy genius-agent with agent-os-genesis".

Install mode	Command
Bare-metal, prod (PyPI)	uvx genius-agent-mcp · or uv tool install genius-agent
Bare-metal, dev (editable)	uv pip install -e ".[all]" · or pip install -e ".[all]"
Container, prod	deploy knucklessg1/genius-agent:latest via docker-compose / swarm / podman / podman-compose / kubernetes
Container, dev (editable)	deploy docker/compose.dev.yml (source-mounted at /src; edits live on restart)

Secrets are read-existing + seeded via vault_sync — you are only prompted for what's missing.