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markovo-mcp

markovo-mcp

by fisher-byte
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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markovo_convert

Convert supported files or authorized public HTTPS pages into clean, structured Markdown via an account-metered API with credit limits and a configured root directory.

Instructions

Convert a supported file through the account-metered Markovo API.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input_path": "<input_path>",
      "out_dir": "<out_dir>",
      "max_credits": "<max_credits>"
    },
    "name": "markovo_convert"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNofast
out_dirYes
input_pathYes
max_creditsYes
capability_idNo
download_formatNozip
layout_fidelityNoOpt-in formula-region Beta for PDFs. Detected equations are returned as LaTeX and must be reviewed against the original.standard

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full disclosure burden, and it only hints that the call is credit-metered. It omits whether conversion is asynchronous (the existence of markovo_job_status/markovo_job_assets siblings strongly implies a job-returning workflow), what happens to files already in out_dir, permission needs, and rate limits.

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?

A single front-loaded sentence with no filler or repetition. It is efficient, though it errs toward under-specification rather than over-verbosity.

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?

For a 7-parameter, 3-required conversion tool with no annotations and no output schema, the description is far too thin. It never explains what a call returns (job handle vs converted asset), how it relates to job_status/job_assets, or how credits are consumed against max_credits.

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

Parameters2/5

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

Schema description coverage is 14% (only layout_fidelity is documented), so the description must compensate and adds no parameter meaning at all. Ambiguous fields like max_credits (cost ceiling? abort behavior?), capability_id (required or inferred?), and mode ('fast' vs 'accurate' tradeoff) are left unexplained.

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 names a specific verb and resource ('Convert a supported file'), which is clearer than a tautology. It implicitly distinguishes itself from markovo_convert_url by scoping input to a file, but never explicitly names that sibling or the split between them.

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?

There is no when-to-use guidance, no prerequisites (API key, credit balance), and no routing to alternatives such as markovo_convert_url for remote sources. The agent must infer usage entirely from the name and schema.

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

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