Jestor MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Jestor through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Jestor "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Jestor?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Jestor MCP Server
Empower your AI agents with Jestor's low-code internal tools platform. This MCP server allows you to list objects (tables), retrieve and list records, manage users, and monitor workflows and dashboards directly through the Jestor API. Ideal for automating internal operations and database management.
Pydantic AI validates every Jestor tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
The Jestor MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Jestor to Pydantic AI via MCP
Follow these steps to integrate the Jestor MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Jestor with type-safe schemas
Why Use Pydantic AI with the Jestor MCP Server
Pydantic AI provides unique advantages when paired with Jestor through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Jestor integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Jestor connection logic from agent behavior for testable, maintainable code
Jestor + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Jestor MCP Server delivers measurable value.
Type-safe data pipelines: query Jestor with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Jestor tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Jestor and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Jestor responses and write comprehensive agent tests
Jestor MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Jestor to Pydantic AI via MCP:
get_me
Use this to verify connection status and current permissions. Gets current authenticated user info
get_object
Useful for understanding field types and relationships within a specific table. Retrieves details/schema for a specific object
get_record
Essential for deep-diving into a specific entry in the database. Retrieves details for a specific record
list_apps
Useful for discovering high-level toolsets available to the user. Lists all installed internal apps
list_dashboards
Use this to identify where aggregated data visualizations are located. Lists all configured dashboards
list_objects
Returns object names and labels. Use this to discover available datasets before querying specific records. Lists all objects (tables) in your Jestor account
list_records
This is the primary tool for browsing data within a table (e.g., listing all "Tasks" or "Clients"). Lists records for a specific object
list_users
Returns names, emails, and IDs. Useful for identifying record owners or system administrators. Lists all users in the organization
list_webhooks
Use this to audit third-party integrations. Lists all configured webhooks
list_workflows
Useful for auditing system logic and event-driven actions. Lists all automated workflows
Example Prompts for Jestor in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Jestor immediately.
"List all objects in my Jestor account."
"Show me the records for the 'Invoices' object."
"Check the status of my workflows."
Troubleshooting Jestor MCP Server with Pydantic AI
Common issues when connecting Jestor to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiJestor + Pydantic AI FAQ
Common questions about integrating Jestor MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Jestor with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Jestor to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.