Simple Gong MCP server
Gong MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Simple 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.
You will need 2 environment variables: GONG_ACCESS_KEY, GONG_ACCESS_SECRET. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by kenazk; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Variable | Description | Required |
|---|---|---|
| GONG_ACCESS_KEY | Credential the server authenticates with. | Yes |
| GONG_ACCESS_SECRET | Credential the server authenticates with. | Yes |
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Microsoft's official browser automation server — drive a real browser through the accessibility tree, no screenshots needed.
GitHub's official server — repos, issues, pull requests, Actions and code security, straight from your assistant.
Issue tracking at the speed of conversation — Linear's official hosted server with OAuth and zero install.
Local repository surgery — status, diffs, commits, branches and history for any repo on disk.
Timezone sanity for AI — current time anywhere and correct conversions, without the model doing date math.