Pipedrive Deals 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 Pipedrive Deals 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 Deals "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Pipedrive Deals?"
)
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 Deals MCP Server
Connect Pipedrive CRM to any AI agent — manage your entire sales pipeline without switching tabs.
Pydantic AI validates every Pipedrive Deals 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
- 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 Deals 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 Pipedrive Deals to Pydantic AI via MCP
Follow these steps to integrate the Pipedrive Deals 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 Pipedrive Deals with type-safe schemas
Why Use Pydantic AI with the Pipedrive Deals MCP Server
Pydantic AI provides unique advantages when paired with Pipedrive Deals 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 Deals 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 Deals connection logic from agent behavior for testable, maintainable code
Pipedrive Deals + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Pipedrive Deals MCP Server delivers measurable value.
Type-safe data pipelines: query Pipedrive Deals with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Pipedrive Deals tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Pipedrive Deals and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Pipedrive Deals responses and write comprehensive agent tests
Pipedrive Deals MCP Tools for Pydantic AI (12)
These 12 tools become available when you connect Pipedrive Deals to Pydantic AI via MCP:
pd_create_deal
Title is required. Use pd_list_pipelines and pd_list_stages to find pipeline_id and stage_id. Link to existing contacts via person_id and org_id (use search tools to find these). Expected close date uses YYYY-MM-DD format. Create a new deal in Pipedrive with title, value, currency, expected close date, and pipeline/stage placement
pd_deal_followers
Followers receive notification updates about deal changes. Use to check who on the team is tracking a deal or to understand deal visibility across the organization. Get internal team members (users) following a specific deal in Pipedrive for visibility tracking
pd_deal_participants
Participants are contacts involved in the deal beyond the primary contact — e.g., decision makers, influencers, legal reviewers. Use when the user asks "who is involved in this deal?" or needs stakeholder information. Get all persons (contacts) participating in a specific Pipedrive deal
pd_deal_timeline
Use for trend analysis: "how many deals were created this month?", "show deal velocity over the last 12 weeks". Interval can be day/week/month, amount is the number of periods to look back. Get deal creation trends over time — how many deals were added per day, week, or month in a pipeline
pd_deals_by_pipeline
Use when the user wants to see all deals in a specific sales process (e.g., "show all deals in the Enterprise pipeline"). Find pipeline IDs using pd_list_pipelines. Get all deals in a specific pipeline for pipeline-level analysis and reporting
pd_deals_by_stage
Returns deals with title, value, persons, and orgs at that stage. Use for questions like "what deals are in Proposal?" or "how much is in Negotiation?". Find stage IDs using pd_list_stages. Get all deals at a specific pipeline stage for bottleneck analysis, forecasting, or stage-specific review
pd_delete_deal
This is permanent and removes all associated data. Consider using pd_update_deal with status="deleted" for soft-delete instead. Use only when the user explicitly wants to permanently remove a deal. Permanently delete a deal from Pipedrive — this action cannot be undone
pd_get_deal
Returns full deal data including title, value, stage, pipeline, linked persons/orgs, expected close date, creation date, and all custom fields. Use after searching to drill into a specific deal. Get the complete details of a specific Pipedrive deal by ID including all custom fields and history
pd_list_pipelines
Use to find pipeline IDs for filtering deals or creating new deals in a specific pipeline. List all sales pipelines in Pipedrive with names, deal counts, and active status
pd_list_stages
Essential for finding stage IDs to create, filter, or move deals. Shows each stage name, its order in the pipeline, and how many deals are at each stage. List stages within a Pipedrive pipeline showing names, display order, and deal counts per stage
pd_search_deals
Returns deal title, monetary value, currency, pipeline stage, pipeline name, linked person, and organization. Use when the user wants to find a specific deal or check pipeline status. Search Pipedrive deals by title or keyword to find opportunities with value, stage, pipeline, and linked contacts
pd_update_deal
Advance stage_id to move deals forward. Set status to "won" or "lost" to close. Update value after negotiation. Only specified fields change. Update a Pipedrive deal — advance stage, change value, or mark as won/lost to reflect pipeline progress
Example Prompts for Pipedrive Deals in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Pipedrive Deals immediately.
"Search for deals with Acme Corp"
"Create a call activity for tomorrow at 2pm"
"Show me the pipeline stages"
Troubleshooting Pipedrive Deals MCP Server with Pydantic AI
Common issues when connecting Pipedrive Deals to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiPipedrive Deals + Pydantic AI FAQ
Common questions about integrating Pipedrive Deals 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 Deals 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 Pipedrive Deals to Pydantic AI
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.