Forecast MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Forecast through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Forecast Assistant",
instructions=(
"You help users interact with Forecast. "
"You have access to 6 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Forecast"
)
print(result.final_output)
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 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.
The OpenAI Agents SDK auto-discovers all 6 tools from Forecast through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Forecast, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Forecast MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 6 tools from Forecast
Why Use OpenAI Agents SDK with the Forecast MCP Server
OpenAI Agents SDK provides unique advantages when paired with Forecast through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Forecast + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Forecast MCP Server delivers measurable value.
Automated workflows: build agents that query Forecast, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Forecast, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Forecast tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Forecast to resolve tickets, look up records, and update statuses without human intervention
Forecast MCP Tools for OpenAI Agents SDK (6)
These 6 tools become available when you connect Forecast to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting Forecast to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Forecast + OpenAI Agents SDK FAQ
Common questions about integrating Forecast MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Forecast 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 Forecast to OpenAI Agents SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.
