Bring Predictive Scheduling
to Pydantic AI
Learn how to connect LiquidPlanner Classic to Pydantic AI and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the LiquidPlanner Classic MCP Server?
Connect your LiquidPlanner Classic workspace to any AI agent and manage project planning through natural conversation.
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
How it works
1. Subscribe to this server
2. Enter your LiquidPlanner email, password, and Workspace ID
3. Start managing projects from Claude, Cursor, or any MCP-compatible client
Who is this for?
- PMs — manage predictive project schedules
- Teams — track tasks and time entries
- Executives — monitor deadline forecasts and resource allocation
Built-in capabilities (10)
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
Why Pydantic AI?
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.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your LiquidPlanner Classic integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your LiquidPlanner Classic connection logic from agent behavior for testable, maintainable code
LiquidPlanner Classic in Pydantic AI
LiquidPlanner Classic and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect LiquidPlanner Classic to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for LiquidPlanner Classic in Pydantic AI
The LiquidPlanner Classic 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. All 10 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
LiquidPlanner Classic for Pydantic AI
Every tool call from Pydantic AI to the LiquidPlanner Classic MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I manage tasks with predictive scheduling?
Yes. Create tasks with best/worst case estimates. LiquidPlanner calculates predictive schedules and deadline probabilities automatically.
Does LiquidPlanner Classic require three credentials?
Yes. Requires Email, Password, and Workspace ID. Uses HTTP Basic Auth (email:password) against app.liquidplanner.com/api/workspaces/{id}.
Can I track time entries?
Yes. Access logged time entries per task and team member with effort hours and date ranges.
How does Pydantic AI discover MCP tools?
Create an 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?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your LiquidPlanner Classic MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai