Formester MCP Server

Connect AI agents directly to your Formester form submissions via the Model Context Protocol (MCP).

The Formester MCP server lets AI models — including Claude, GPT-4, and any MCP-compatible agent — read submissions, analyze file attachments, search historical data, and write AI-generated insights back to your records. No custom API integration required.

Overview

Property	Value
Name	`formester`
Version	`1.0.0`
Endpoint	`/mcp`
Transport	HTTP/SSE (streaming) or STDIO
Auth	Bearer token (per-user, per-scope)

Quickstart

1. Generate a token

In your Formester account, go to API (from the home page) and click Generate API Token. You can scope it to your full account or restrict it to a single form.

2. Connect your AI agent

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "formester": {
      "command": "npx",
      "args": ["mcp-remote", "https://app.formester.com/mcp"],
      "env": {
        "BEARER_TOKEN": "your_token_here"
      }
    }
  }
}

STDIO transport:

BEARER_TOKEN=your_token_here npx mcp-remote https://app.formester.com/mcp

Tools

`read_submission`

Read a single form submission by ID.

Scope: submission.read
Returns: All field values, custom fields, status, spam flag, timestamps
Set include_files: true to include file attachment metadata (IDs, filenames, URLs)
File content is not returned here — use fetch_file for that

`update_submission`

Write AI-generated data back to a submission as custom fields.

Scope: submission.write
Supported types: shorttext, longtext, number, date, time, radio, checkbox, multiple-checkbox
Auto-creates new custom columns if they don't exist
Cannot overwrite original form submission fields — only custom fields

`query_submissions`

Search and filter multiple submissions from a form.

Scope: submission.read
Filters: date range, starred, spam, custom field value
Paginated: limit (max 100) + offset, returns total_count and has_more
Use to find similar past submissions, analyze trends, or build context before processing a new one

`fetch_file`

Download and return the contents of a file attachment.

Scope: submission.read
Images (PNG, JPG, GIF, WebP, SVG) → base64 for vision-capable AI models
PDFs → extracted text, page by page (or base64 if extract_text: false)
Text files (TXT, MD, CSV, JSON, XML, HTML) → raw text
Audio/Video → base64
Max file size: 10 MB
Also returns metadata: image dimensions, PDF page count, author, etc.

Auth & Security

Bearer token passed via Authorization: Bearer <token> header
Tokens are scoped per user and optionally restricted to a single form
Scopes: submission.read and/or submission.write
last_used timestamp tracked per token

Typical Workflow

1. Trigger (webhook / scheduled task / manual)
2. read_submission       → get all field data for a submission
3. fetch_file            → read uploaded documents, images, or CVs
4. query_submissions     → find similar past submissions for context
5. [Agent processes data and generates insights]
6. update_submission     → write results (scores, labels, summaries) back to the record

Example use cases

Job application screening — read CV attachments, score candidates, save results as custom fields
Lead qualification — analyze contact form submissions, enrich with company data, flag high-priority leads
Support triage — classify incoming requests by category and urgency, route automatically
Survey analysis — run sentiment analysis across all responses, tag themes, export insights

# Formester MCP Server

# Overview

# Quickstart

# 1. Generate a token

# 2. Connect your AI agent

# Tools

# read_submission

# update_submission

# query_submissions

# fetch_file

# Auth & Security

# Typical Workflow

# Example use cases

# Links