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Overview

You can access mkinf hub Agents throught the mkinf python SDK or via REST API calls.

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1. Find an AI Agent

Browse available AI Agents at mkinf hub and select an agent that matches your use case Repository card showing an AI Agent

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2. Copy the pull command

Check the “Use Agent” section of your chosen repository for import instructions Card showing how to import the AI Agent

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Python

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Import the AI Agent

To import the agents in our platform, follow this structure: 
from mkinf import hub as mh
tools = mh.pull(["owner/repository"])
Some tools require environment variables, including API keys, which must be created and set before use. 
from mkinf import hub as mh
tools = mh.pull(
    ["ScrapeGraphAI/scrapegraphai"],
    env={
        "SCRAPEGRAPH_LLM_MODEL": "openai/gpt-4o-mini",
        "SCRAPEGRAPH_LLM_API_KEY": os.getenv("OPENAI_API_KEY")
    },
    timeout=120
)
You can even set an execution timeout, the default execution timeout is 60 seconds.
Remember to configure any required environment variables specified in the agent’s documentation.
Currently, mkinf tools are compatible with LangChain chains and graphs. Support for other frameworks like CrewAI, AutoGen, and SmolAgents is coming soon.

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REST API

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Request execution

Agents actions can also be executed directly via API call. 
curl -X POST "https://run.mkinf.io/v0.1/<REPO_OWNER>/<REPO_NAME>:<REPO_VERSION>/<REPO_ACTION>" \
  -H "Authorization: Bearer $MKINF_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "args": { "your_arg_key": "your_arg_value" },
    "env": { "your_env_key": "your_env_value" },
    "timeout": 60
  }'
Note that you have also to include the input arguments, you can them in the input schema of each action. Card showing AI Agent input and output schema

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Next Steps