About
The HubSpot MCP Server bridges AI assistants with your HubSpot account, enabling direct CRUD operations on contacts and companies while providing semantic search and caching to improve performance and reliability.
Capabilities
HubSpot MCP Server
The HubSpot MCP Server bridges Claude and other AI assistants with the HubSpot CRM ecosystem, allowing developers to perform CRUD operations on contacts, companies, and deals, as well as retrieve sales analytics directly from the AI workflow. By exposing a rich set of tools that mirror HubSpot’s REST endpoints, this server eliminates the need for manual API integration and lets conversational agents query or update CRM data on demand.
What Problem Does It Solve?
Many sales teams rely heavily on HubSpot for lead management, pipeline tracking, and performance reporting. Traditionally, accessing this data requires writing custom scripts or using HubSpot’s own UI, which can be time‑consuming and error‑prone. The MCP server solves this by providing a standardized, AI‑friendly interface: developers can call high‑level tools such as or without worrying about authentication, pagination, or data mapping. This accelerates prototyping of intelligent assistants that can answer sales questions, suggest next actions, or automate routine updates.
Core Capabilities
- Contact Management – Search, retrieve, create, and update contacts with fine‑grained property control.
- Company Management – List or fetch company details, supporting pagination and selective fields.
- Deal Operations – Create, read, update, and list deals, including support for custom properties and pipeline filtering.
- Sales Analytics – Aggregate metrics over configurable time periods (daily to yearly) and filter by pipeline, stage, or owner.
- Deal History – Retrieve the full change log for a deal, enabling audit trails and context‑aware suggestions.
These tools are exposed through the MCP tool schema, so Claude can invoke them by name and pass JSON arguments. The server handles authentication via HubSpot OAuth, automatically refreshing tokens as needed.
Why It Matters for Developers
Integrating HubSpot into AI workflows becomes a matter of adding the MCP server to your environment and declaring the desired tools. Developers can:
- Build Conversational Sales Assistants that ask for a contact’s latest deal status or update a lead score without leaving the chat.
- Automate Workflows by triggering when a new email is received or updating deal stages based on sentiment analysis.
- Generate Real‑Time Reports by calling during a meeting to show current pipeline health.
- Maintain Data Integrity with and , ensuring that AI‑generated changes are reflected in the CRM instantly.
Real‑World Use Cases
- Lead Qualification Bot: An AI agent evaluates incoming leads, searches for existing contacts, and creates or updates records with enriched attributes.
- Pipeline Health Dashboard: A conversational dashboard that pulls monthly sales metrics and highlights bottlenecks, prompting the user to take corrective actions.
- Deal Closure Assistant: When a deal reaches a specific stage, the assistant automatically logs a follow‑up task or sends a personalized email using HubSpot’s transactional templates.
- Audit and Compliance: Retrieving deal history enables compliance teams to review changes in real time, ensuring that automated updates are traceable.
Unique Advantages
- Unified Toolset: All HubSpot interactions are encapsulated in a single MCP server, reducing fragmentation across multiple APIs.
- Zero‑Code Integration: Developers can add the server to their MCP environment without writing wrapper code, letting AI assistants discover and use the tools directly.
- Extensible: The tool list can be expanded to cover additional HubSpot entities (tickets, workflows) or custom endpoints as the platform evolves.
- Security‑First: OAuth scopes are requested only for the operations needed, and token rotation is handled transparently.
In summary, the HubSpot MCP Server empowers AI assistants to become powerful sales collaborators—fetching insights, updating records, and automating routine tasks—all within a conversational context.
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