Sally MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Add Comment, Check Sally Health, Create Project, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Sally 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 Sally app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 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 Sally "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Sally?"
)
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 Sally MCP Server
Connect your Sally instance to any AI agent and take full control of your API-first project management through natural conversation.
Pydantic AI validates every Sally 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
- Projects — Create, list, and inspect projects with full metadata.
- Tasks — Full CRUD with priorities (P1-P4), statuses, labels, and assignees.
- Comments — Add comments to any task for collaboration and status updates.
- Kanban Board — Retrieve the aggregated board view showing tasks organized by status columns.
- Timesheets — Access timesheet reports with tracked hours and billing information.
- Profile — Verify your authenticated identity and workspace permissions.
The Sally 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.
All 12 Sally tools available for Pydantic AI
When Pydantic AI connects to Sally through Vinkius, your AI agent gets direct access to every tool listed below — spanning task-management, kanban, api-first, 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.
Comments are visible to all project members. Add a comment to a task
Check Sally instance health
Create a new project
Optionally set priority (P1-P4), status, and labels. Create a new task in a project
Get the Kanban board view
Get the authenticated user profile
Get details of a specific project
Get full details of a specific task
Get timesheet report for the workspace or project
List all projects in the workspace
Optionally filter by project ID to see tasks for a specific project. List tasks, optionally filtered by project
Only provided fields are changed. Update an existing task
Connect Sally to Pydantic AI via MCP
Follow these steps to wire Sally 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 Sally MCP Server
Pydantic AI provides unique advantages when paired with Sally 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 Sally integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Sally connection logic from agent behavior for testable, maintainable code
Sally + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Sally MCP Server delivers measurable value.
Type-safe data pipelines: query Sally with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Sally tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Sally and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Sally responses and write comprehensive agent tests
Example Prompts for Sally in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Sally immediately.
"List all projects in my Sally workspace."
"Create a P2 task 'Implement auth middleware' in project proj_abc123 with labels 'backend, security'."
"Show me the Kanban board for project proj_abc123."
Troubleshooting Sally MCP Server with Pydantic AI
Common issues when connecting Sally to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiSally + Pydantic AI FAQ
Common questions about integrating Sally 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.