SketricGen MCP Server for Pydantic AIGive Pydantic AI instant access to 18 tools to Check Sketricgen Status, Delete Conversation, Get Agent, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect SketricGen through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The SketricGen app connector for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 18 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 SketricGen "
"(18 tools)."
),
)
result = await agent.run(
"What tools are available in SketricGen?"
)
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 SketricGen MCP Server
Empower your AI agents to securely orchestrate complex workflows using the SketricGen platform. With 18 dedicated tools, your AI can now programmatically trigger multi-agent tasks, inject relevant contacts into context, construct searchable knowledge bases, and granularly inspect execution traces.
Pydantic AI validates every SketricGen tool response against typed schemas, catching data inconsistencies at build time. Connect 18 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.
What you can do
- Execute complex multi-agent workflows programmatically
- Create and query vector-searchable knowledge bases
- Debug executions with full tracing capabilities
- Track tool calls and credit consumption per run
- Access and manage CRM-style contact profiles
- Maintain distinct conversation histories
Who is it for?
Designed for AI engineers, prompt designers, and automation teams seeking an advanced orchestration layer with full traceability for complex agentic workflows.The SketricGen MCP Server exposes 18 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.
All 18 SketricGen tools available for Pydantic AI
When Pydantic AI connects to SketricGen through Vinkius, your AI agent gets direct access to every tool listed below — spanning workflow-automation, multi-agent-systems, knowledge-base, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Delete conversation
Get agent details
Get contact details
Get conversation
Get knowledge base
Get trace details
Get trace credit usage
Get workflow details
List AI agents
List contacts
List conversations
List knowledge bases
List templates
List execution traces
List workflows
Run AI workflow
Run workflow for contact
Connect SketricGen to Pydantic AI via MCP
Follow these steps to wire SketricGen into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the SketricGen MCP Server
Pydantic AI provides unique advantages when paired with SketricGen 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 SketricGen integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your SketricGen connection logic from agent behavior for testable, maintainable code
SketricGen + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the SketricGen MCP Server delivers measurable value.
Type-safe data pipelines: query SketricGen with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple SketricGen tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query SketricGen and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock SketricGen responses and write comprehensive agent tests
Example Prompts for SketricGen in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with SketricGen immediately.
"Run my customer support agent workflow in SketricGen with the question 'How do I reset my password?'"
"Show me the execution trace and credit usage for my last SketricGen workflow run."
"List all knowledge bases in SketricGen and show which agents are connected to each."
Troubleshooting SketricGen MCP Server with Pydantic AI
Common issues when connecting SketricGen to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSketricGen + Pydantic AI FAQ
Common questions about integrating SketricGen 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.