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Gong MCP Server

Gong MCP Server

Local
github.com/kenazkBusiness & Marketing39Updated 82w ago

About Gong MCP Server

Gong MCP Server is an MCP server that provides access to Gong's API for retrieving call recordings and transcripts. It lets Claude query Gong data through a standardized interface, suited to teams that review sales calls.

Key features

  1. 01List Gong calls with date range filtering
  2. 02Retrieve detailed transcripts for specific calls
  3. 03Authenticate with Gong API credentials
  4. 04Standardized MCP interface for Claude

Use cases

  1. 01Review sales calls from a given period
  2. 02Summarize call transcripts with Claude
  3. 03Analyze customer conversations inside Claude

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"gong": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"build"
]
}
}
}
Run commanddocker run -i --rm build

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocibuild

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Gong MCP Server

A Model Context Protocol (MCP) server that provides access to Gong's API for retrieving call recordings and transcripts. This server allows Claude to interact with Gong data through a standardized interface.

Features

  • List Gong calls with optional date range filtering
  • Retrieve detailed transcripts for specific calls
  • Secure authentication using Gong's API credentials
  • Standardized MCP interface for easy integration with Claude

Prerequisites

  • Node.js 18 or higher
  • Docker (optional, for containerized deployment)
  • Gong API credentials (Access Key and Secret)

Installation

Local Development
  1. Clone the repository
  2. Install dependencies:
    npm install
    
  3. Build the project:
    npm run build
    
Docker

Build the container:

docker build -t gong-mcp .

Configuring Claude

  1. Open Claude Desktop settings
  2. Navigate to the MCP Servers section
  3. Add a new server with the following configuration:
{
  "command": "docker",
  "args": [
    "run",
    "-it",
    "--rm",
    "gong-mcp"
  ],
  "env": {
    "GONG_ACCESS_KEY": "your_access_key_here",
    "GONG_ACCESS_SECRET": "your_access_secret_here"
  }
}
  1. Replace the placeholder credentials with your actual Gong API credentials from your .env file

Available Tools

List Calls

Retrieves a list of Gong calls with optional date range filtering.

{
  name: "list_calls",
  description: "List Gong calls with optional date range filtering. Returns call details including ID, title, start/end times, participants, and duration.",
  inputSchema: {
    type: "object",
    properties: {
      fromDateTime: {
        type: "string",
        description: "Start date/time in ISO format (e.g. 2024-03-01T00:00:00Z)"
      },
      toDateTime: {
        type: "string",
        description: "End date/time in ISO format (e.g. 2024-03-31T23:59:59Z)"
      }
    }
  }
}
Retrieve Transcripts

Retrieves detailed transcripts for specified call IDs.

{
  name: "retrieve_transcripts",
  description: "Retrieve transcripts for specified call IDs. Returns detailed transcripts including speaker IDs, topics, and timestamped sentences.",
  inputSchema: {
    type: "object",
    properties: {
      callIds: {
        type: "array",
        items: { type: "string" },
        description: "Array of Gong call IDs to retrieve transcripts for"
      }
    },
    required: ["callIds"]
  }
}

License

MIT License - see LICENSE file for details

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.