Practical overview
When it fits
Use it when you need a concrete, inspectable starting point for an agent prototype or want to compare implementation patterns across frameworks, protocols and model providers.
Who it is for
- Developers exploring autonomous agents in Python
- Builders prototyping LLM, payment or Web3-enabled workflows
- Hackathon participants seeking a prepared project starting point
- Contributors sharing agent implementations
Documented uses
- Prototype an autonomous Python agent
- Explore multi-agent coordination with uAgents or A2A
- Build agentic workflows with MCP, LangChain or CrewAI
- Adapt examples for Gemini, Claude or OpenAI
- Investigate Agentverse-oriented implementations, payments and RAG workflows
Requirements & limits
The repository is public. The quickstart requires Git, pip and Python 3.10 or later; individual examples may require service-specific API keys.
- Choose by implementation area: the repository separates quickstarts, LLM integrations, A2A, MCP, payments, RAG and multi-agent systems.
- Check each folder's README, requirements and .env.example because dependencies and credentials vary by example.
- The code is Python-based, with repository tooling including a setup script and Docker configuration.
- The README displays an Apache 2.0 license badge, while repository metadata identifies an MIT license; inspect the repository license before reuse.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Set up the hackathon quickstarter example
Prepare the documented quickstarter project and launch its example agent.
Before you start
- Git
- Python 3.10 or later
- pip
- API keys required by the selected example
Steps
Clone the repository and change into its directory.
Enter the fetch-hackathon-quickstarter folder.
Create and activate a Python virtual environment, then install the folder's requirements.
Copy .env.example to .env and add the required API keys.
Run agents/alice/agent.py, or use the repository setup.sh script for the quickstarter setup.
Expected outcome
The selected quickstarter environment is prepared and the Alice agent is invoked using the repository's documented command.
Guide limitations
- Required credentials depend on the selected example.
- The guide covers the repository's documented quickstarter path; other folders can have different dependencies and environment variables.
Compare options for Agent orchestration
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Fetch.ai Innovation Lab Examples | Prototype an autonomous Python agent | CLI, Desktop, Self-hosted, Server | The repository is public. The quickstart requires Git, pip and Python 3.10 or later; individual examples may require service-specific API keys. |
| Agenite | Define typed tools with JSON Schema validation and error handling. | CLI | |
| Veldra | Create an agent with a policy, tools, skills, knowledge base and reasoning method. | Self-hosted | The documented deployment is self-hosted and uses a sign-in gate after a first-run administrator account is created. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 4 October 2026
- Original website title
- fetchai/innovation-lab-examples · Official homepage title · retained in its source language