office_docs_mcp

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word_search

Find specific text in Word documents by searching paragraphs and tables. Specify file path and query to locate matches, with optional case sensitivity and result limits.

Instructions

Search for a text query across Word paragraphs and tables.

Args:
    file_path: Path to the Word document (.docx).
    query: Text to search for.
    case_sensitive: Whether matching is case-sensitive (default: False).
    max_results: Maximum results to return (default: 50).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes
`file_path`	Yes
`max_results`	No
`case_sensitive`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Sep 27, 2026

TDQS

A3.7/5.0

Behavior3/5

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

No annotations are present, so the description must carry behavioral disclosure. It does state the search scope (paragraphs and tables), the case_sensitive default, and the max_results cap, but it never explicitly says the operation is read-only or describes behavior for no matches or result truncation.

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

Conciseness5/5

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

The purpose is front-loaded in one clear sentence, followed by a compact, focused Args list. There is no filler or redundant commentary; every line contributes usable information.

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

Completeness3/5

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

Because an output schema exists, explaining return values is unnecessary. However, the description lacks usage context, alternatives, and any explicit assurance about read-only behavior or search limitations, which are the main remaining gaps for an agent deciding when to invoke this tool.

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

Parameters4/5

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

Schema description coverage is 0%, so the Args section meaningfully compensates: file_path is clarified as a .docx path, query is described as text to search for, and both optional parameters get human-readable semantics. It mostly restates schema titles/defaults rather than adding deeper matching details, so it stops short of 5.

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?

Opens with a specific verb and resource: 'Search for a text query across Word paragraphs and tables.' This clearly identifies the document type and content scope, and distinguishes search from sibling read/table tools by describing a search operation rather than a read or mutation operation.

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 gives no when-to-use guidance and names no alternatives. An agent is not told to choose word_search over word_read_paragraphs or word_replace_text, nor that excel_search and ppt_search cover other document formats.

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