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Mcp Editor

What is MCP (Model Context Protocol)?

The Model Context Protocol (MCP) is an open standard that defines how AI applications communicate with external tools and services. Think of it as a "USB-C port for AI" — instead of every AI app building custom integrations for every tool, MCP provides a single, standardized protocol.

This editor is the power-user companion to the guided MCP Config Generator. Where the generator walks you through a wizard, the editor lets you work directly with the raw mcpServers JSON, convert the same config between client formats, and validate it before dropping it into your AI app.

Edit, Validate, Convert

JSON-First Editing

The editor is built around the MCP config JSON. You can:

  • Paste an existing claude_desktop_config.json, opencode.json, .cursor/mcp.json, or VS Code settings.json
  • Switch to the form view to add, remove, and edit servers without hand-writing JSON
  • Watch validation errors and warnings update as you type

Multi-Server, Multi-Client

A single config can contain many servers. The editor keeps them all in one place and converts the whole document for whichever client you target:

Client Config File Root Key
Claude Desktop claude_desktop_config.json mcpServers
OpenCode opencode.json mcpServers
Cursor .cursor/mcp.json mcpServers
VS Code settings.json mcp.servers
Other mcp-config.json mcpServers

Switching the target client rewrites the output (including the VS Code mcp.servers key) without touching your source config.

Validation & Health Checks

The editor reuses the same validation engine as the generator:

  • JSON syntax checking
  • Per-server checks (command for stdio, url for sse/http)
  • Empty-secret warnings for env vars that look sensitive
  • Template-matched health checks (missing tokens, Node/uv requirements, OS notes)

Environment Variables & .env.example

Secrets never belong in committed config. The editor collects every env key across all servers and generates a .env.example you can copy or download, so you can keep real values out of version control.

Shareable Configs

Copy a share link to send a config to a teammate. The entire config is compressed into the URL hash with lz-string — nothing is uploaded to any server.

Security Best Practices

  1. Use dedicated tokens: Create API tokens with minimal required scopes instead of using personal access tokens
  2. Read-only when possible: For databases, create a read-only user if you only need query access
  3. Restrict filesystem access: Only grant access to directories the AI actually needs to read
  4. Review permissions: Check the health checks before adding any MCP server
  5. Revoke unused access: Remove MCP server configs you no longer use
  6. Keep tokens secret: MCP configs contain tokens — use .env.example and don't commit real values

Resources