Compatible with every major AI agent and IDE
Pd create deal on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive Deals
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 on Pipedrive 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 on Pipedrive Deals
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
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
Can I create and update records?
Yes! Create and update deals, contacts, activities, and notes — all through natural conversation.
Can I audit what my AI agents are doing with this integration?
Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.
How does the AI access my passwords and credentials?
It simply doesn't. On Vinkius, your passwords, API keys, and login details are kept in a secure vault. The AI (like ChatGPT or Claude) merely "asks" Vinkius to perform the task. Vinkius opens the door, does the work, and hands the result back to the AI. Your credentials are never seen, read, or learned by the artificial intelligence.
Supported Use Cases for Pipedrive Deals
Build automated workflows with Cursor and Claude Code by connecting to the Pipedrive Deals MCP server.
Autonomous deal management via AI
The Pipedrive Deals MCP translates LLM intent into specific deal management actions. Agents like Cursor use this to interface securely with your sales crm infrastructure.
Next-Gen pipeline tracking Automation
Add pipeline tracking functionality to your custom chatbots. The Pipedrive Deals MCP handles the payload formatting required for ChatGPT and Claude to interface with sales crm endpoints.
Pipedrive Deals. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
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.
Explore More MCP Servers
View all →
Accept Language Parser
1 toolsParse HTTP Accept-Language headers into priority-ordered language preferences with quality weights.

OpenFGA (Fine-Grained Auth)
16 toolsManage fine-grained authorization with OpenFGA — create stores, define authorization models, and manage relationship tuples directly from your AI agent.

Medium
10 toolsPublish and manage content on Medium — create posts and manage publications directly from any AI agent.

Northflank (Developer Cloud & Orchestration)
10 toolsManage cloud infrastructure via Northflank — deploy microservices, trigger CI builds, and audit background jobs.
