form fill-mcp

fill_form

Fill a PDF form with the given field values and save the result to disk.

WORKFLOW: 1) Call list_form_fields first to get exact field names and their x/y positions.
2) Use position coordinates to confirm which field is which — higher y = higher on page.
3) Pass exact field names from list_form_fields here. Never guess field names.

Use for single-page or short forms (under 5 pages). Use fill_form_multipage for longer forms.

Returns ok:false with unknown_fields if ALL provided field names are invalid.
Returns ok:true with a warnings.unknown_fields list if SOME names are invalid (partial fill).

Input Schema

TableJSON Schema

Name	Required	Description
`api_key`	No	Your FormFill API key (get one at formfill.plenitudo.ai).
`pdf_path`	Yes	Absolute path to the source PDF file.
`output_path`	Yes	Absolute path where the filled PDF will be saved.
`field_values`	Yes	Map of field names to values. Use list_form_fields to discover field names.
`payment_proof`	No	x402 payment proof (tx hash). Alternative to api_key for pay-per-use.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the transparency burden. It discloses return behavior for invalid and partially invalid field names (ok:false with unknown_fields vs ok:true with warnings.unknown_fields), plus the partial fill edge case. This goes beyond basic function and is valuable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a WORKFLOW section, usage limits, and return behavior. It's slightly longer than necessary but every sentence conveys meaningful operational detail. The main purpose is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and rich parameter descriptions, the description adds critical workflow context, alternative tool guidance, and error-handling nuances. It is fully sufficient for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds useful context about using exact field names from list_form_fields and interpreting y-coordinates, but this mostly reinforces existing schema guidance for field_values rather than introducing new parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Fill a PDF form with the given field values and save the result to disk', which is a specific verb+resource. It also distinguishes from siblings by explicitly naming fill_form_multipage for longer forms and list_form_fields for field discovery.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance: 'Use for single-page or short forms (under 5 pages). Use fill_form_multipage for longer forms.' It also prescribes a workflow of calling list_form_fields first, including never guessing field names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All form fill-mcp tools Inspect

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TDQS

A4.3/5.0

Disambiguation4/5

Tools are mostly distinct: list_form_fields and extract_form_data read form structure/values, fill_form and fill_form_multipage handle filling with clear usage boundaries, and flatten_form finalizes. The two fill tools share purpose but are explicitly differentiated by document length and complexity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: extract_form_data, fill_form, fill_form_multipage, flatten_form, list_form_fields. The naming clearly indicates the action and target, with no mixed conventions.

Tool Count5/5

Five tools cover the essential PDF form workflow (inspect, read, fill, flatten) without redundancy. The count is well-scoped for the server's purpose.

Completeness5/5

The tool surface covers the full lifecycle of working with PDF forms: listing fields, extracting data, filling single- or multi-page forms, and flattening. No critical operations are missing for common form-filling scenarios.

Resources

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