Pipedrive Activities MCP Server for Pydantic AI 8 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Pipedrive Activities 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 Pipedrive Activities "
"(8 tools)."
),
)
result = await agent.run(
"What tools are available in Pipedrive Activities?"
)
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 Pipedrive Activities MCP Server
Connect Pipedrive CRM to any AI agent — manage your entire sales pipeline without switching tabs.
Pydantic AI validates every Pipedrive Activities tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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
- Deals — Search, create, and update deals with pipeline tracking
- Contacts — Find and create persons with email, phone, and organization
- Organizations — Search companies linked to deals and contacts
- Activities — Create calls, meetings, tasks, and emails
- Notes — Attach notes to deals, persons, or organizations
- Pipelines — View all pipeline stages and deal flow
The Pipedrive Activities MCP Server exposes 8 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 Pipedrive Activities to Pydantic AI via MCP
Follow these steps to integrate the Pipedrive Activities 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 8 tools from Pipedrive Activities with type-safe schemas
Why Use Pydantic AI with the Pipedrive Activities MCP Server
Pydantic AI provides unique advantages when paired with Pipedrive Activities 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 Pipedrive Activities integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Pipedrive Activities connection logic from agent behavior for testable, maintainable code
Pipedrive Activities + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Pipedrive Activities MCP Server delivers measurable value.
Type-safe data pipelines: query Pipedrive Activities with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Pipedrive Activities tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Pipedrive Activities and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Pipedrive Activities responses and write comprehensive agent tests
Pipedrive Activities MCP Tools for Pydantic AI (8)
These 8 tools become available when you connect Pipedrive Activities to Pydantic AI via MCP:
pd_activity_types
Default types: call, meeting, task, deadline, email, lunch. Teams can add custom types. Use to discover available activity types before creating activities, especially in accounts with custom configurations. List all activity types configured in Pipedrive — both default types (call, meeting) and custom types defined by the team
pd_create_activity
Subject and type are required. Type must be: call, meeting, email, task, lunch, or deadline (use pd_activity_types to see custom types). Set due_date (YYYY-MM-DD), due_time (HH:MM), and duration (HH:MM). Link to deals, persons, or orgs. Activities appear in the Pipedrive calendar and task queue for the assigned user. Schedule a sales activity in Pipedrive — a call, meeting, email follow-up, task, lunch, or deadline linked to deals or contacts
pd_deal_activities
Returns all scheduled, pending, and completed activities for that deal. Use when the user asks "what activities are on this deal?", "when is the next meeting for this deal?", or needs to review the engagement history of an opportunity. Get all activities (calls, meetings, tasks) linked to a specific deal for a complete activity history
pd_delete_activity
Consider marking as done (pd_mark_activity_done) instead to preserve history. Use only when the user explicitly wants to remove an activity from the record. Permanently delete a Pipedrive activity — this removes it from history and cannot be undone
pd_get_activity
Returns subject, type, dates/times, duration, notes, linked deal/person/org, and completion status. Use after listing activities to drill into a specific item. Get complete details of a specific Pipedrive activity by ID including notes, duration, and linked records
pd_list_activities
Returns subject, type (call/meeting/email/task/lunch/deadline), due date and time, whether it is done, and linked deal/person/org. Filter by done status: "true" for completed, "false" for pending/upcoming. Use when the user asks about tasks to do, scheduled meetings, overdue items, or recent sales activity. List Pipedrive activities (calls, meetings, tasks, emails) with due dates, types, and completion status
pd_mark_activity_done
The activity remains in history but is no longer in the pending/overdue queue. Use when the user says they completed a call, finished a meeting, or done with a task. Mark a Pipedrive activity as completed — removes it from the pending task queue and logs it as done
pd_update_activity
Only specified fields change. Use to reschedule (change due_date), rename (change subject), or reclassify (change type). Does not mark as done — use pd_mark_activity_done for that. Update an existing Pipedrive activity — reschedule, rename, or change type
Example Prompts for Pipedrive Activities in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Pipedrive Activities immediately.
"Search for deals with Acme Corp"
"Create a call activity for tomorrow at 2pm"
"Show me the pipeline stages"
Troubleshooting Pipedrive Activities MCP Server with Pydantic AI
Common issues when connecting Pipedrive Activities to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiPipedrive Activities + Pydantic AI FAQ
Common questions about integrating Pipedrive Activities 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 Pipedrive Activities 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.
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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 Pipedrive Activities to Pydantic AI
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.