@gudlab/gud-api-mcp — Gud API for AI agents

A Model Context Protocol server that lets any MCP-capable AI agent — Claude Code, Cursor, Windsurf, Codex, Cline, Zed, and others — create, run, and save API requests and collections as real Gud API files your team can open in any VS Code-compatible editor.

When an agent builds an endpoint, it registers the request, runs it, and captures the response as an example. The collection is written to your project's .gud-api/ folder — the same files the Gud API extension reads. Open your editor and every endpoint the agent built is in your sidebar, ready to click and re-run. It's git-committable, so it travels with the PR.

Neither Postman nor Bruno occupies this lane: agent-written, editor-native, git-friendly, no cloud account.

Works with

• MCP clients (this server): Claude Code, Cursor, Windsurf, Codex, Cline, Zed, Continue — any tool that speaks the Model Context Protocol.
• Editors (the companion Gud API extension that reads the files): VS Code, plus any VS Code-compatible editor that installs from Open VSX — Cursor, Windsurf, VSCodium, Antigravity, Trae, and more.

The server itself is editor-agnostic — it just writes files. You don't need the extension to use it, but the extension is what makes the collections clickable.

Install

The server runs via npx — no global install needed. It's the same config for every MCP client; only the file it lives in differs.

Add this to your client's MCP config (.mcp.json for Claude Code, ~/.cursor/mcp.json for Cursor, the Windsurf/Codex/Cline equivalent, etc.):

{
  "mcpServers": {
    "gud-api": {
      "command": "npx",
      "args": ["-y", "@gudlab/gud-api-mcp", "--project", "."]
    }
  }
}

--project . scopes all reads/writes to the current project's .gud-api/ folder. Pass an absolute path to target a different project.

What the agent can do

Tool	Purpose
list_collections	List collections with request counts and folders
get_collection	Full contents of one collection (bodies + example summaries)
create_collection	Create a collection in .gud-api/collections
upsert_request	Create/update a request (matched by name), nest under a folder path
send_request	Execute a request, resolve {{variables}}, run tests, optionally capture an example
delete_request	Remove a saved request
upsert_environment	Create/update a named variable set (base_url, tokens), optionally set active
get_active_environment	Read active variables — secret-looking values are masked

How it fits the Gud API format

Files are written byte-compatible with the extension (v0.5.7+): slug filenames (payments-api.json), canonical key order, schemaVersion, trailing newline. The MCP server targets workspace scope — files live in your project and are never cloud-synced, so agent output stays local and reviewable.

Captured responses are stored as examples[] on each request (max 5). The extension renders these read-only so you can see exactly what the API returned when the agent tested it.

Security notes

• send_request executes arbitrary HTTP — no more than the curl access an agent already has, but be aware of it.
• Secret masking: get_active_environment masks values whose keys look like secrets (token, key, secret, password, …). send_request still resolves the real values server-side, so the agent can use a credential without reading it into its context. This is heuristic, not a guarantee — don't put production credentials in an agent-visible environment.
• Cookies are in-memory per session — an agent never inherits your browser session cookies.
• Writes are confined to --project — collection/environment names are slugified, so a name can't traverse out of the .gud-api/ folder.

Links

• Docs: https://gudapi-docs.gudlab.org/guide/ai-agents
• Gud API extension: VS Code Marketplace · Open VSX
• Issues: https://github.com/gudlab/gud-api/issues

License

Proprietary — see the LICENSE file. Free to install and use; redistribution and modification are restricted.