Celoxis MCP Server for Pydantic AI 12 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Celoxis 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 Celoxis "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Celoxis?"
)
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 Celoxis MCP Server
Connect your Celoxis enterprise platform to any AI agent and take full control of your Project Portfolio Management (PPM) workflow through natural conversation.
Pydantic AI validates every Celoxis tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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
- Project & Portfolio Mapping — List strategic portfolios and extract granular project structures including absolute timelines, completion statuses, and mapped budget blocks.
- WBS & Tasks — Retrieve explicit Work Breakdown Structure nodes, identifying active assignments, task health, and explicit phase deliverables.
- Resource Allocation — Evaluate working resources, parse user mappings, and expose global scheduling types and distinct system roles across your organization.
- Timesheets & Accounting — Accurately pull time entries logged by members to measure billable matrices and ledger associations tied directly to tasks natively.
- Issue & Risk Governance — Poll blocking issues preventing workflows and assess graded severity impacts modeled inside the Celoxis organizational risk matrix.
- Approvals Pipeline — Interrogate pending validations routing over timesheets, assessing gating rules and internal clearance statuses immediately.
The Celoxis MCP Server exposes 12 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 Celoxis to Pydantic AI via MCP
Follow these steps to integrate the Celoxis 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 12 tools from Celoxis with type-safe schemas
Why Use Pydantic AI with the Celoxis MCP Server
Pydantic AI provides unique advantages when paired with Celoxis 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 Celoxis integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Celoxis connection logic from agent behavior for testable, maintainable code
Celoxis + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Celoxis MCP Server delivers measurable value.
Type-safe data pipelines: query Celoxis with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Celoxis tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Celoxis and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Celoxis responses and write comprehensive agent tests
Celoxis MCP Tools for Pydantic AI (12)
These 12 tools become available when you connect Celoxis to Pydantic AI via MCP:
get_project
Get an explicit Celoxis project and its complete intrinsic properties structure by ID
list_approvals
List explicit tracking objects identifying pending/cleared approvals over timesheets and expenses constraints
list_clients
List explicit top-level CRM organizational clients linked internally to distinct portfolios
list_expenses
List raw billable/non-billable expenses physically mapped onto task items inside the ecosystem
list_issues
List custom app items representing blocked issues explicit to complex workflows mapping problems
list_milestones
List raw milestones natively mapping absolute phase delivery tracking inside the WBS
list_portfolios
List strategic global tracking Portfolios mapping top-level aggregates over child projects natively
list_projects
List all top-level project portfolio items in Celoxis. Returns physical IDs, names, status, and timeline data
list_resources
List all explicit Celoxis working resources parsing the core user mappings handling allocations
list_risks
List explicit organizational risks bounded natively via the Celoxis custom application matrix
list_tasks
List comprehensive Work Breakdown Structure (WBS) tasks representing concrete deliverables within active projects
list_time_entries
List actual time entries logged explicitly against Celoxis tasks or projects for accounting
Example Prompts for Celoxis in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Celoxis immediately.
"List all active projects in our company portfolio and check their timeline status."
"Check the detailed logged time entries for the Marketing project and verify pending approvals."
"Extract the explicit risk logs and blocked issues reported across our client portfolio."
Troubleshooting Celoxis MCP Server with Pydantic AI
Common issues when connecting Celoxis to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiCeloxis + Pydantic AI FAQ
Common questions about integrating Celoxis 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 Celoxis 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 Celoxis to Pydantic AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.