Codearkt
Implementation of the CodeAct agentic framework with Docker containers for security, MCP servers for tool integrations, and multi-agent support.
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CodeArkt
CodeArkt is a battery-included implementation of the CodeAct framework with support for the multi-agent architecture. Ship autonomous agents that can reason, write, execute & iterate over code. All from a single Python package.
β¨ Why CodeArkt?
- Multi-agent orchestration β coordinate hierarchies of specialist agents.
- Secure Python sandbox β secure, ephemeral Docker execution environment for code actions.
- First-class tool ecosystem β auto-discover & register MCP tools.
- Drop-dead simple UI β launch an elegant Gradio chat or run the terminal client.
- Production ready β typed codebase (
mypy --strict), CI, tests, Docker & Apache-2.0 license.
π Quick Start
Install the package:
pip install codearkt # requires Python β₯ 3.12
Run your MCP servers:
python -m academia_mcp --port 5056 # just an example MCP server
Run a server with a simple agent and connect it to your MCP servers:
import os
from codearkt.codeact import CodeActAgent
from codearkt.llm import LLM
from codearkt.server import run_server
# Use your own or remote MCP servers
mcp_config = {
"mcpServers": {"academia": {"url": "http://0.0.0.0:5056/mcp", "transport": "streamable-http"}}
}
# Create an agent definition
api_key = os.getenv("OPENROUTER_API_KEY", "")
assert api_key, "Please provide OpenRouter API key!"
agent = CodeActAgent(
name="manager",
description="A simple agent",
llm=LLM(model_name="deepseek/deepseek-chat-v3-0324", api_key=api_key),
tool_names=["arxiv_download", "arxiv_search"],
)
# Run the server with MCP proxy and agentic endpoints
run_server(agent, mcp_config, port=5055)
Now run a Python client:
from codearkt.client import query_agent
from codearkt.llm import ChatMessage
history = [ChatMessage(role="user", content="Find an abstract of the 2402.01030 paper")]
for event in query_agent(history, port=5055):
if event.content:
print(event.content, end="", flush=True)
Within seconds, you will see agents collaborating, executing Python snippets, and streaming the results back to your console.
You can also use existing clients, Gradio and terminal:
uv run -m codearkt.terminal --port 5055
uv run -m codearkt.gradio --port 5055
π§© Feature Overview
| Area | Highlights |
|---|---|
| Agents | Hierarchical manager / worker pattern, pluggable prompts, configurable iteration limits |
| Tools | Automatic discovery via MCP registry, Python execution (python_interpreter) |
| Execution | Sandboxed temp directory, timeout, streamed chunks, cleanup hooks |
| Observability | AgentEventBus publishes JSON events β integrate with logs, websockets, or GUI. Opentelemetry is also supported. |
| UI | Responsive Gradio Blocks chat with stop button, syntax-highlighted code & output panels |
| Extensibility | Compose multiple CodeActAgent instances, add your own LLM backend, override prompts |
π Documentation
For now, explore the well-typed source code.
π οΈ Project Structure
codearkt/
ββ codeact.py # Core agent logic
ββ python_executor.py # Secure sandbox for arbitrary code
ββ event_bus.py # Pub/Sub for agent events
ββ gradio.py # Optional web UI
ββ ...
examples/
ββ multi_agent/ # End-to-end usage demos
π€ Contributing
Pull requests are welcome! Please:
- Fork the repo & create your branch:
git checkout -b feature/my-feature - Install dev deps:
make install - Run the linter & tests:
make validate && make test - Submit a PR and pass the CI.
Join the discussion in Discussions or open an Issue.
π License
CodeArkt is released under the Apache License 2.0 β see the LICENSE file for details.
