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mcp-docparser

mcp-docparser

by Jasonzld
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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chunk_document

Split document files or extracted text into configurable character chunks with overlap to prepare content for processing.

Instructions

Split document or extracted text into chunks for processing

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": {
      "file_path": "<file_path>"
    },
    "name": "chunk_document"
  }
}

Input Schema

NameRequiredDescriptionDefault
overlapNoOverlap between chunks
file_pathYesPath to the document file
chunk_sizeNoSize of each chunk in characters

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden but discloses almost nothing beyond the core action. It does not say whether chunks are returned inline or written to disk, what the output shape is, or what happens for large files or missing paths. 'For processing' is vague filler rather than behavioral context.

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 tight sentence with the action front-loaded and no redundant clauses. Its brevity is efficient, though the space saved is partly the space that should have held output and usage detail.

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 3-parameter tool with no output schema and no annotations, the description should clarify the return value (a list of chunk strings? file paths?) and any constraints on input size or file type. None of that is present, so an agent cannot fully predict the result of a call.

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%, and the schema already documents chunk_size as characters with a default of 1000 and overlap with a default of 100. The description adds nothing about units, limits, or how overlap interacts with chunk_size, so the baseline 3 applies.

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 states a specific verb ('Split') and resource ('document or extracted text') plus the outcome ('into chunks'), so it is distinguishable from siblings like parse_document or extract_text. It stops short of explicitly contrasting itself with those siblings, which keeps it from a 5.

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 guidance on when to chunk versus parse or extract, no mention of prerequisites, and no indication of what the caller should do with the produced chunks. Usage is only implied by the tool name.

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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