Agentia: Ergonomic LLM Agents
Ergonomic LLM Agents with MCP and Skills support.
Getting Started
Run agents with tools, MCP, and Skills
from agentia import Agent, MCP
from typing import Annotated
# Define a tool as a python function
def get_weather(location: Annotated[str, "The city name"]):
"""Get the current weather in a given location"""
return { "temperature": 72 }
# Declare a MCP server:
calc = MCP(name="calculator", command="uvx", args=["mcp-server-calculator"])
# Create an agent
# This will load the function tool, the calculator MCP, and all skills under $CWD/.skills
agent = Agent(model="openai/gpt-5-nano", tools=[get_weather, calc], skills=True)
# Run the agent with the mcp
response = await agent.run("Calculate 234 ** 3")
print(response.text)
# Output: The result of 234 raised to the power of 3 is 12,812,904.
The Magic Decorator
Create agent-powered magic functions.
Support both plain types and pydantic models as input and output.
from agentia import magic
from pydantic import BaseModel
class Forcast(BaseModel):
location: str
temperature_celsius: int
@magic
async def get_weather(weather_forcast: str) -> Forcast:
"""Create weather forcase object based on the input string"""
...
forcast = await get_weather("The current temperature in Boston is 72°F")
print(forcast.location) # Output: Boston
print(forcast.temperature_celsius) # Output: 22
Supported Parameter and Result Types
- Any types that can be passed to
pydantic.TypeAdaptor:- Builtin types:
int,float,str,bool,tuple[_],list[_],dict[_, _] - Enums:
Literal['A', 'B', ...],StrEnum,IntEnum, andEnum - dataclasses
- Builtin types:
pydantic.BaseModelsubclasses
1 maintainer
Release files for agentia 0.1.41
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agentia-0.1.41.tar.gz | 39.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agentia-0.1.41-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 92.5 kB
Release files / agentia-0.1.41.tar.gz
| Download URL | agentia-0.1.41.tar.gz |
|---|---|
| Size | 39.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.10.4 {"installer":{"name":"uv","version":"0.10.4","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
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Release files / agentia-0.1.41-py3-none-any.whl
| Download URL | agentia-0.1.41-py3-none-any.whl |
|---|---|
| Size | 52.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9f561ca5acbe1eede2fee1aa8ef2d5be48a1338d33624c108437f9a5f56676d2
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.10.4 {"installer":{"name":"uv","version":"0.10.4","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"macOS","version":null,"id":null,"libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}
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