LiquidPlanner Classic MCP Server for Pydantic AIGive Pydantic AI instant access to 10 tools to Create Project, Create Task, Get Project, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect LiquidPlanner Classic 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 LiquidPlanner Classic app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 10 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 LiquidPlanner Classic "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in LiquidPlanner Classic?"
)
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 LiquidPlanner Classic MCP Server
Connect your LiquidPlanner Classic workspace to any AI agent and manage project planning through natural conversation.
Pydantic AI validates every LiquidPlanner Classic 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.
What you can do
- Task Management — Create, update, and assign tasks with priority and estimates
- Project Tracking — Browse projects, milestones, and deliverables
- Timeline Monitoring — Track predictive schedules and deadline forecasts
- Workspace Browsing — Navigate workspace structure and team members
- Time Tracking — Access logged time and effort data
The LiquidPlanner Classic 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.
All 10 LiquidPlanner Classic tools available for Pydantic AI
When Pydantic AI connects to LiquidPlanner Classic through Vinkius, your AI agent gets direct access to every tool listed below — spanning predictive-scheduling, resource-leveling, task-dependencies, 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.
Create a new project in the default workspace
Requires parent_id if it should be nested under a project or folder. Create a new task in the default workspace
Get details of a specific project
Get details of a specific task
Uses the default configured workspace if no ID is provided. Get details of a specific workspace or the default workspace
List members in the default workspace
List projects in the default workspace
List tasks in the default workspace
List workspaces from LiquidPlanner Classic
Update an existing task in the default workspace
Connect LiquidPlanner Classic to Pydantic AI via MCP
Follow these steps to wire LiquidPlanner Classic 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 LiquidPlanner Classic MCP Server
Pydantic AI provides unique advantages when paired with LiquidPlanner Classic 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 LiquidPlanner Classic integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your LiquidPlanner Classic connection logic from agent behavior for testable, maintainable code
LiquidPlanner Classic + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the LiquidPlanner Classic MCP Server delivers measurable value.
Type-safe data pipelines: query LiquidPlanner Classic with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple LiquidPlanner Classic tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query LiquidPlanner Classic and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock LiquidPlanner Classic responses and write comprehensive agent tests
Example Prompts for LiquidPlanner Classic in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with LiquidPlanner Classic immediately.
"Show all projects and the predicted schedule for the Platform v2 project."
"Create a task and show time tracking for the team this week."
"Show workspace members and resource allocation."
Troubleshooting LiquidPlanner Classic MCP Server with Pydantic AI
Common issues when connecting LiquidPlanner Classic to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiLiquidPlanner Classic + Pydantic AI FAQ
Common questions about integrating LiquidPlanner Classic 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.