Can my agent list all active projects in Forecast?

Yes. Use the 'list_projects' tool. The agent will retrieve the global array of all managed projects mapped inside your Forecast account, including their names and unique IDs.

How do I check a specific team member's availability via chat?

Use the 'list_people' tool. Your agent will fetch the physical identity definitions and availability constraints of global members, allowing you to monitor team utilization and workload natively.

Can I see the upcoming milestones for a project through the agent?

Absolutely. Use the 'list_milestones' tool with the specific Project ID. The agent will identify timebox markers bounding specific sprint or deliverable targets for that project natively.

Forecast MCP Server for Pydantic AI 6 tools — connect in under 2 minutes

Name: Forecast
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 6 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Forecast through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Forecast "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Forecast?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Forecast MCP Server

Connect your Forecast.app account to any AI agent and take full control of your resource management and project scheduling through natural conversation.

Pydantic AI validates every Forecast tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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 Orchestration — Retrieve the global array of all managed projects and fetch comprehensive scheduling and resource states belonging to specific project IDs natively
Task Lifecycle Auditing — Enumerate specific physical tasks allocated under project IDs to track work completion and identify bottlenecks synchronously
Personnel Oversight — Fetch physical identity definitions and availability constraints of global members to manage team utilization and workload limits securely
Client Relationship Mapping — Extract explicit client relationships mapped to projects inside your account to manage stakeholder communications flawlessly
Milestone Tracking — Identify timebox markers bounding specific sprint or deliverable targets to ensure project timelines remain within active boundaries
Resource Allocation Discovery — Analyze specific localized variables decoding active assignments and extracting hidden structural constraints across your portfolio
Operational Metadata retrieval — Access global account metadata and project-level attributes to verify workspace configurations natively

The Forecast MCP Server exposes 6 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 Forecast to Pydantic AI via MCP

Follow these steps to integrate the Forecast 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 6 tools from Forecast with type-safe schemas

Why Use Pydantic AI with the Forecast MCP Server

Pydantic AI provides unique advantages when paired with Forecast 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 Forecast integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Forecast connection logic from agent behavior for testable, maintainable code

Forecast + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Forecast MCP Server delivers measurable value.

Type-safe data pipelines: query Forecast with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Forecast tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Forecast and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Forecast responses and write comprehensive agent tests

Forecast MCP Tools for Pydantic AI (6)

These 6 tools become available when you connect Forecast to Pydantic AI via MCP:

get_project

Get project details

list_clients

List clients

list_milestones

List milestones

list_people

List people

list_projects

List projects

list_tasks

List tasks

Example Prompts for Forecast in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Forecast immediately.

"List all active projects in Forecast"

"Show me the tasks for project 'API V2 Development'"

"Who is available this week for a new assignment?"

Troubleshooting Forecast MCP Server with Pydantic AI

Common issues when connecting Forecast to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Forecast + Pydantic AI FAQ

Common questions about integrating Forecast MCP Server with Pydantic AI.

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 Forecast MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.