This MCP server provides JavaScript execution capabilities with a modern runtime.
This MCP server provides JavaScript execution capabilities with a modern runtime. The codebench mcp mcp server wraps that behind the Model Context Protocol, so an assistant can use it through 3 defined tools rather than through you.
Everything the assistant can do here goes through one of these:
Installation — The Installation tool exposed by this serverUsage — The Usage tool exposed by this serverexecuteJS — // Basic JavaScript execution const result = 2 + 3; console.log('Result:', result);ghcr.io/mark3labs/codebench-mcp on a container image is all you need. Most clients run it directly, so configuration is a few lines and a restart.
This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Codebench MCP's toolset — Installation, Usage, executeJS — is a fair guide to whether it matches your workflow. It is maintained by mark3labs; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Installation | The Installation tool exposed by this server. |
| Usage | The Usage tool exposed by this server. |
| executeJS | // Basic JavaScript execution const result = 2 + 3; console.log('Result:', result); |
{
"mcpServers": {
"codebench": {
"command": "docker",
"args": ["run", "-i", "--rm", "ghcr.io/mark3labs/codebench-mcp"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.