gibsonai.py
"""GibsonAI MCP Server - Create and manage databases with prompts
This example shows how to connect a local GibsonAI MCP to Agno agent.
You can instantly generate, modify database schemas
and chat with your relational database using natural language.
From prompt to a serverless database (MySQL, PostgresQL, etc.), auto-generated REST APIs for your data.
Example prompts to try:
- "Create a new GibsonAI project for my e-commerce app"
- "Show me the current schema for my project"
- "Add a 'products' table with name, price, and description fields"
- "Create a 'users' table with authentication fields"
- "Deploy my schema changes to production"
How to setup and run:
1. Install [UV](https://docs.astral.sh/uv/) package manager.
2. Install the GibsonAI CLI:
```bash
uvx --from gibson-cli@latest gibson auth login
```
3. Install the required dependencies:
```bash
uv pip install agno mcp openai
```
4. Export your API key:
```bash
export OPENAI_API_KEY="your_openai_api_key"
```
5. Run the GibsonAI agent by running this file.
6. Check created database and schema on GibsonAI dashboard: https://app.gibsonai.com
This logs you into the [GibsonAI CLI](https://docs.gibsonai.com/reference/cli-quickstart)
so you can access all the features directly from your agent.
"""
import asyncio
from textwrap import dedent
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.mcp import MCPTools
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
async def run_gibsonai_agent(message: str):
"""Run the GibsonAI agent with the given message."""
mcp_tools = MCPTools(
"uvx --from gibson-cli@latest gibson mcp run",
timeout_seconds=300, # Extended timeout for GibsonAI operations
)
# Connect to the MCP server
await mcp_tools.connect()
agent = Agent(
name="GibsonAIAgent",
model=OpenAIChat(id="gpt-4o"),
tools=[mcp_tools],
description="Agent for managing database projects and schemas",
instructions=dedent("""\
You are a GibsonAI database assistant. Help users manage their database projects and schemas.
Your capabilities include:
- Creating new GibsonAI projects
- Managing database schemas (tables, columns, relationships)
- Deploying schema changes to hosted databases
- Querying database schemas and data
- Providing insights about database structure and best practices
"""),
markdown=True,
)
# Run the agent
await agent.aprint_response(message, stream=True)
# Close the MCP connection
await mcp_tools.close()
# Example usage
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
asyncio.run(
run_gibsonai_agent(
"""
Create a database for blog posts platform with users and posts tables.
You can decide the schema of the tables without double checking with me.
"""
)
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U "agno[mcp]" openai
3
Prepare uvx
Install uv, then verify
uvx is available:uvx --version
4
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
5
Authenticate GibsonAI
Install the Gibson CLI and authenticate before starting its MCP server:
uvx --from gibson-cli@latest gibson auth login
6
Run the example
Save the code above as
gibsonai.py, then run:python gibsonai.py