Skip to main content
Glama

Frenchie

by io.github.Lab94

OCR to Markdown

ocr_to_markdown

Convert PDF/image files into Markdown through Frenchie

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoOptional Frenchie API key (fr_...). Falls back to the FRENCHIE_API_KEY env var when omitted.
file_pathNoAbsolute local file path. Stdio transport only — over HTTP, upload via upload_file first and pass uploaded_file_reference instead.
uploaded_file_referenceNoObject key returned by upload_file. Required for HTTP transport; ignored when file_path is provided in stdio.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdNo
resultNo
statusYes
creditsUsedNo
resultExpiresAtNo
estimatedCompletionNo

TDQS

C2.9/5.0
Behavior2/5

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

The description only says 'through Frenchie', implying an external service, but does not disclose behavioral traits such as potential side effects, network usage, or whether files are modified. Annotations indicate readOnlyHint false, but the description adds no further context beyond the raw conversion action.

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 a single concise sentence, front-loaded with the action and resource, making it easy to scan. It earns its place with no filler, though it could be slightly augmented for behavioral context without losing conciseness.

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

Completeness2/5

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

Given the moderate complexity (3 optional params, output schema, annotations), the description is too brief and omits usage guidance, behavioral context, and differentiation from siblings. The schema and output schema cover parameters and return values, but the overall tool context remains incomplete.

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?

The input schema fully documents all three parameters with detailed descriptions, so the baseline is 3. The description adds no additional parameter semantics beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states the tool converts PDF/image files into Markdown, identifying the core action and resource/output format. It mentions 'through Frenchie' indicating an external service, but it does not explicitly contrast with sibling tools like extract_to_markdown or transcribe_to_markdown.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites such as file upload for HTTP transport. The schema covers parameter details, but usage context is entirely absent.

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

All Frenchie toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: extracting structured documents, OCR, transcription, image generation, file upload, result file download, and job status retrieval. The descriptions provide clear boundaries, so an agent can easily select the right tool.

Naming Consistency5/5

Tool names follow a consistent snake_case pattern with verb-first names (e.g., extract_to_markdown, generate_image, upload_file). Conversion tools share the _to_markdown suffix, while utility tools use verb_noun, creating a predictable and readable convention.

Tool Count5/5

Seven tools is well-scoped for a file conversion and image generation server. Each tool addresses a distinct need without redundancy or bloat, making the set feel complete yet focused.

Completeness4/5

The tool surface covers the main workflows: converting documents, images, audio/video to Markdown, generating images, and handling file uploads and downloads. A minor gap is that get_job_result only fetches the latest job, lacking support for retrieving specific job results by ID, which could hinder multi-job workflows.

Resources