mcpField
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Chat-first form service with 127 MCP tools. Create, manage, and analyze forms entirely through conversation.

Chat-first form service with 127 MCP tools. Create, manage, and analyze forms entirely through conversation.

Remote
github.com/formlovaAI & Agents1Updated 11w ago
Repository

About Chat-first form service with 127 MCP tools. Create, manage, and analyze forms entirely through conversation.

formlova-mcp is a CLI helper for configuring the FORMLOVA remote MCP service, aimed at developers and teams setting up form workflows in projects. It generates client configuration and checks connectivity, but does not run the service or perform OAuth.

Key features

  1. 01Prints client setup snippets
  2. 02Writes supported project-level config files
  3. 03Checks MCP URL reachability
  4. 04Checks common local config files

Use cases

  1. 01Generate FORMLOVA MCP config for a project
  2. 02Standardize local MCP setup across a team or repo
  3. 03Troubleshoot reachability of the remote service

MCP support

The CLI helps clients connect to FORMLOVA's remote MCP server at `https://formlova.com/api/mcp`. It is not an MCP server and does not complete client authentication or OAuth.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://formlova.com/api/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

127
ParameterTypeRequiredDescription
categoryenumNoFilter by category (omit for all)event | business | survey | education | community

Details

From the project README

formlova-mcp

Connect FORMLOVA to any MCP-compatible AI client without hand-writing setup files.

FORMLOVA is a chat-first form operations service. Most form tools stop at creation — FORMLOVA starts after publish. It covers the full post-publish lifecycle: response management, follow-up emails, reminders, A/B tests, email sequences, LINE messaging, analytics, team management, and more — all from your AI chat.

138 MCP tools across 24 categories. Works with Claude, ChatGPT, Codex, Claude Code, Cursor, Gemini CLI, Windsurf, and any MCP-compatible client.

formlova-mcp is not the FORMLOVA server. It is a small CLI helper for setup snippets, project-level config files, and a quick connectivity check.

The fastest path

Most users do not need this package.

If your AI client already has an MCP add screen, use this URL directly:

https://formlova.com/api/mcp

Reviewing setup instructions and registering the URL does not require a FORMLOVA account. On first real use, you can log in or sign up during authentication.

If you want a CLI helper instead, start here:

npx -y formlova-mcp print --client all

If you want project-level config files written for supported developer tools:

npx -y formlova-mcp install --client all --scope project --yes

This writes config files only. Authentication still begins inside the client on first use, and some clients require a restart or reconnect before the tools appear.

What this package is for

  • Print copy-paste setup snippets for supported clients
  • Generate project-level config files for common developer tools
  • Check whether the FORMLOVA MCP URL is reachable from your machine
  • Standardize local MCP setup across a team or repo

Supported clients

This package provides setup helpers for:

  • ChatGPT
  • Claude
  • Codex
  • Claude Code
  • Cursor
  • Gemini CLI
  • Windsurf

Any MCP-compatible client can connect with the same URL — the list above is not a limitation:

https://formlova.com/api/mcp

Command overview

CommandPurposeWrites files
printShow setup snippets for one or more clientsNo
installWrite supported project-level config filesYes
doctorCheck MCP URL reachability and local config presenceNo
print

Print setup snippets only. No files are written.

npx -y formlova-mcp print --client codex
npx -y formlova-mcp print --client claude-code
npx -y formlova-mcp print --client cursor
npx -y formlova-mcp print --client chatgpt
npx -y formlova-mcp print --client gemini-cli
install

Write project-level setup files for supported developer tools.

npx -y formlova-mcp install --client all --scope project --yes

install does not complete OAuth or client-side authentication for you.

Current write targets:

ClientPath written by install
Codex.codex/config.toml
Claude Code.mcp.json
Cursor.cursor/mcp.json

For ChatGPT and Gemini CLI, install prints setup guidance because there is no stable local config file target in this package.

doctor

Check MCP URL reachability and common local config files.

npx -y formlova-mcp doctor

Client setup references

ChatGPT
  • Enable developer mode first
  • Then open Settings > Apps > Advanced settings (Create app) and add the MCP server URL
  • Docs: OpenAI remote MCP guide
Claude
Codex
codex mcp add formlova --url https://formlova.com/api/mcp
Claude Code
claude mcp add --transport http formlova https://formlova.com/api/mcp
Cursor

You can use the normal MCP UI, or a config file such as:

{
  "mcpServers": {
    "formlova": {
      "url": "https://formlova.com/api/mcp"
    }
  }
}
Gemini CLI
gemini mcp add --transport http formlova https://formlova.com/api/mcp

What it does not do

  • It does not run a local FORMLOVA MCP server
  • It does not replace the normal web-based setup flow for ChatGPT or Claude
  • It does not complete client-side authentication or OAuth on your behalf
  • It does not auto-write user-level config yet

Requirements

  • Node.js 18.17+

Notes

Client-side setup menus and steps may change without notice. When in doubt, ask your AI client how to add an MCP server, then use:

https://formlova.com/api/mcp

Links

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.