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Gongio MCP

Query Gong calls, transcripts, summaries, users, workspaces, trackers, and library folders through MCP tools.

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Install Gongio MCP

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "gongio-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "gongio-mcp"
      ],
      "env": {
        "GONG_ACCESS_KEY": "YOUR_VALUE_HERE",
        "GONG_ACCESS_KEY_SECRET": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Automated check passed— started and listed 15 tools correctly (25d ago).

Overview

gongio-mcp MCP server exposes Gong.io data to Claude and other MCP-compatible clients through Gong API credentials. It supports call discovery, metadata, AI summaries, speaker-attributed transcripts, transcript search, user lookup, workspaces, trackers, and call library folders. Use it when an agent needs to investigate sales calls, retrieve conversation details, or filter Gong records by dates, accounts, opportunities, participants, and other criteria. It runs with Node.js or Docker and communicates through standard MCP client configuration.

Use cases

  • Search calls for customer, participant, or opportunity context
  • Retrieve summaries and action items from sales calls
  • Read exact speaker-attributed transcript sections
  • Inspect Gong users, workspaces, and keyword trackers
  • Find calls saved in public library folders

Key features

  • Gong call listing and metadata retrieval
  • AI-generated call summaries
  • Paginated speaker-attributed transcripts
  • Structured and transcript keyword search
  • User, workspace, tracker, and library folder access
  • Search output size safeguards

Tools15

What Gongio MCP lets your agent do. Expand a tool for its parameters.

Verified live~4.2k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

11/16 checks healthy over the last 91d

What it can do

From the 15 tools this server returned when we ran it; 15 declare their own safety hints.

Makes network requests · 15Read-only tools · 15
Network at startup3 connections
Files written at startupNone
Install scriptsNone
npm provenanceSigned build
Package age305 days
Maintainers1

Observed 2026-10-15 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev · gongio-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars22Stargazers on the source repository.
npm downloads11kPackage downloads in the last 30 days.
Last commit12d agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed15Callable tools this server registers over MCP.
Directory activity2 viewsConfig copies, upvotes, and views on AllMCPs.

How Gongio MCP works

What gongio-mcp does

gongio-mcp MCP server connects an MCP client to Gong.io and makes selected Gong data available as agent tools. The available operations cover calls, transcripts, users, workspaces, keyword trackers, and public call library folders.

For call analysis, it can return basic metadata, AI-generated summaries, key points, topics, action items, detailed outlines, and speaker-attributed transcript text. Search functions support filters such as date range, workspace, participant, customer, account email domain, CRM opportunity, title, duration, scope, and transcript keywords.

How it works

The server authenticates to Gong with an access key and secret supplied through environment variables. An MCP-compatible client starts the process, and the client can then invoke the exposed tools with their documented parameters.

Call retrieval is split between lightweight and detailed operations. list_calls returns minimal records and supports date, workspace, and cursor parameters. get_call retrieves metadata for one call, while get_call_summary and get_call_transcript provide progressively richer content. Transcript responses use character-based pagination through maxLength and offset.

search_calls automatically requests multiple API pages, up to roughly 5,000 calls or 50 pages, then applies supported client-side filters. Its default result format includes call metadata, summaries, topics, and participants.

Setup and configuration

Requirements are Node.js 18 or newer, or Docker, plus Gong API credentials. Gong administrators can create an API key from Company Settings, Ecosystem, and API. The access key and secret must both be available when the server starts.

Installation options include running npx gongio-mcp, installing the package globally with npm, building from the repository, or building and running the supplied Docker image. Configure these variables:

  • GONG_ACCESS_KEY
  • GONG_ACCESS_KEY_SECRET

The README provides launch examples for Claude Desktop using either npx or Docker, and for Claude Code using claude mcp add. Repository builds use npm install, npm run build, and node dist/index.js.

Tools and capabilities

The gongio-mcp MCP server includes tools for:

  • Listing calls by date, workspace, or cursor.
  • Retrieving call metadata, AI summaries, and paginated transcripts.
  • Searching calls by structured fields, accounts, opportunities, or transcript text.
  • Listing keyword trackers and workspaces.
  • Listing public library folders and retrieving their saved calls.
  • Getting one user, searching users, or listing workspace users.

Use list_workspaces when another operation requires a workspace ID. Use get_call_summary for an overview and get_call_transcript when exact spoken text is needed.

Limitations and notes

Large searches can exceed the MCP output limit, which defaults to 50,000 characters and can be changed with MAX_MCP_OUTPUT_LENGTH. When that happens, the server falls back to a compact table while retaining call IDs and titles. Narrow the date range, add scope or customer filters, set a minimum duration, or remove expensive content options such as outline.

The outline include option can produce about 80 KB per call, so it is unsuitable for broad searches. Tracker output is limited to matching trackers, or trackers with nonzero counts when no tracker filter is supplied. Transcripts are paginated by default to reduce context size; request later sections with an offset.

Read the full README View source on GitHub

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Frequently Asked Questions about Gongio MCP

gongio-mcp is an MCP server that connects MCP-compatible clients to Gong.io through Gong API credentials. Its main tools list and search calls, retrieve call metadata, AI summaries, and paginated speaker-attributed transcripts, and access users, workspaces, keyword trackers, and public call library folders for agent-driven Gong data queries.

Install it with `npx gongio-mcp`, install it globally with npm, build it from the repository, or build and run the Docker image. Node.js 18+ or Docker is required. Set `GONG_ACCESS_KEY` and `GONG_ACCESS_KEY_SECRET` before starting the server.

Yes, gongio-mcp works with Claude Desktop through an MCP server entry. The documented configuration starts it with either `npx gongio-mcp` or Docker and passes the Gong access key and secret as environment variables.

Narrow the search with date, scope, customer, tracker, or minimum-duration filters, and omit heavy options such as `outline`. If formatted output exceeds `MAX_MCP_OUTPUT_LENGTH`, the server returns a compact table containing call IDs and titles.

Use `get_call_transcript` with the required `callId`. Results are paginated by character count; use `maxLength` to set the requested size and `offset` to retrieve later sections. The default response is 10,000 characters and the documented maximum is 100,000.

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