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How to Use the Freshsales MCP in Mastra AI

Build resilient sales workflows that automatically handle CRM failures using Mastra AI and this integration.

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Mastra AI

Connect Freshsales MCP to Mastra AI

Create your Vinkius account to connect Freshsales to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Automate Freshsales MCP Server Workflows

The `create_lead` tool becomes a reliable step in your Mastra AI automated sequences. If a webhook triggers a new prospect entry, your agent attempts to write it to the CRM. When the API hits a rate limit, the framework's exponential backoff kicks in and retries the request automatically. You can chain this with the `get_lead` tool to verify the entry succeeded. The workflow engine evaluates the response and branches the logic. A successful creation triggers a Slack alert, while a failure routes the payload to an administrator.

Manage Sales Tasks Conditionally

The `list_tasks` tool allows your agent to audit what your sales team needs to accomplish. Mastra can pull this list every morning and evaluate the deadlines. Overdue items get flagged and pushed into a separate escalation workflow. Adding `list_appointments` gives the agent a complete picture of rep availability. The system cross-references scheduled meetings with pending tasks. You build logic that automatically reassigns work if a rep is stuck in calls all afternoon.

Audit Deals and Notes

The `list_deals` tool feeds your workflow engine the current state of the sales pipeline. Your agent pulls the active opportunities and checks them against recent activity logged via `list_notes`. This setup catches stalled deals before they die. If an opportunity shows no new notes in 14 days, Mastra triggers a conditional branch that emails the assigned rep. You handle the entire auditing process without human intervention.

Setup guide

Set up Freshsales MCP in Mastra AI

Prerequisites

  • Node.js 18+ and a TypeScript project
  • @mastra/mcp + @mastra/core packages
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

    Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).

  2. 2

    Configure the MCPClient

    Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

  3. 3

    Discover and inject tools

    Call mcpClient.listTools() and spread the result into your agent's tools object. All Freshsales tools become native Mastra tools.

  4. 4

    Run with any model

    Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "freshsales-alternative-mcp-client",
  servers: {
    "freshsales-alternative-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Freshsales Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Freshsales tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Freshsales transactions"
);
console.log(result.text);

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Freshsales. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Freshsales MCP in Mastra AI

Install `@mastra/mcp@latest` via npm. Initialize the connection using `new MCPClient()` and pass your server URL. Call `mcpClient.listTools()` to spread the CRM operations directly into your agent's toolkit.
You can enable `requireToolApproval` for any write operation. When the agent tries to execute `create_lead`, the workflow pauses until a human reviews and approves the payload.
The framework catches the error and applies exponential backoff. It will retry the `get_contact` or `list_leads` request based on your configuration before routing to a failure branch.
No. The client auto-detects whether your endpoint uses Streamable HTTP or SSE. You just provide the URL and start building your agent logic.
The managed infrastructure isolates every single operation. When your agent fetches revenue numbers via `list_deals` or reads `list_notes`, the execution happens inside a zero-trust sandbox. No data persists on the server after the connection closes.

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