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docx-mcp-server

by bradygaster
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docx-mcp-server

Your Word docs, but you talk to them instead of opening them.

Clone this repo, configure it in 60 seconds, then say "summarize the cloud architecture doc on my desktop" and get back a full topology analysis with a Mermaid diagram. No file paths. No clicking around. Just ask.

Quick Start

git clone https://github.com/bradygaster/docx-mcp-server.git
cd docx-mcp-server
npm install && npm run build

Configure it in Copilot CLI or VS Code, then start talking to your docs.

Related MCP server: MCP Word Commander

Just Talk to It

The old way:
Copy the file path → paste it into a prompt → hope you got the slashes right.

The new way:
"Summarize the cloud architecture doc on my desktop"

And you get this back:

The document describes a three-tier Azure architecture:
- Front-end: Static web apps on Azure CDN
- API layer: Azure Functions with Event Grid for async workflows
- Data tier: Cosmos DB with Redis cache

Key decision: Event-driven architecture for scalability...

Plus a generated Mermaid diagram of the whole topology.

What you can ask

  • "Summarize the demo script I downloaded" → Section-by-section breakdown with key talking points

  • "Search for 'authentication' in the API proposal on my desktop" → Exact matches with surrounding context

  • "What Word docs do I have in Downloads?" → Full list with file sizes and dates

  • "Open the RFP and tell me the deadline" → Reads the doc, finds the date, tells you

What's happening under the hood

You say "cloud architecture doc on my desktop" and the server:

  1. Searches Desktop (including OneDrive-synced folders)

  2. Finds files matching "cloud architecture" (fuzzy, case-insensitive)

  3. Resolves the path and reads the document

  4. Returns the full text to your AI

No file picker. No path copy-paste. Just natural language.

Squad Integration

This repo ships with a pre-configured AI team in the .squad/ directory. If you have @bradygaster/squad installed, you can say:

"Squad, summarize the RFP on my desktop"

And the team reads and analyzes it for you:

  • Keaton (Squad Lead) — Coordinates the team, analyzes document structure and architecture

  • Fenster (Backend Dev) — Handles the document parsing and data extraction

  • Hockney (QA Analyst) — Validates the findings and cross-checks facts

The team collaborates using the same MCP tools — resolve_document, read_document, search_document — but coordinates the work. It's like having three analysts who can read any Word doc you throw at them.

Without Squad: You talk directly to Copilot with docx-mcp-server's tools available.
With Squad: You talk to a team that uses those tools collaboratively to analyze complex documents.

Learn more about Squad →

How It Works

The resolve_document tool is the magic. When you say "cloud architecture doc on my desktop":

  1. Searches the right places — Desktop, Downloads, Documents, current directory, plus OneDrive-synced versions of those folders

  2. Matches flexibly — exact name, prefix match, or substring match (all case-insensitive). Say "quarterly" and it finds Quarterly-Report-Q4.docx

  3. Understands location hints — "on my desktop" or "in downloads" narrows the search

  4. Handles ambiguity — multiple matches? You get a list to pick from

The AI chains tools automatically: resolve the friendly name → read the document → summarize/search/analyze. All from one sentence.

Configure in Copilot CLI

Add to your ~/.copilot/mcp-config.json:

Windows:

{
  "servers": {
    "docx-reader": {
      "command": "node",
      "args": ["C:\\src\\docx-mcp-server\\dist\\index.js"]
    }
  }
}

macOS / Linux:

{
  "servers": {
    "docx-reader": {
      "command": "node",
      "args": ["/home/you/docx-mcp-server/dist/index.js"]
    }
  }
}

Replace the path with the actual location where you cloned the repo.

Configure in VS Code

Add to your .vscode/mcp.json (workspace) or user settings:

Windows:

{
  "servers": {
    "docx-reader": {
      "command": "node",
      "args": ["C:\\src\\docx-mcp-server\\dist\\index.js"]
    }
  }
}

macOS / Linux:

{
  "servers": {
    "docx-reader": {
      "command": "node",
      "args": ["/home/you/docx-mcp-server/dist/index.js"]
    }
  }
}

Available Tools

resolve_document

Finds .docx files by friendly name — the core of the natural language experience. Say "the report on my desktop" and it figures out which file you mean.

Parameter

Type

Required

Description

name

string

yes

Friendly document name, with or without .docx extension (e.g., "report", "cloud architecture")

location

string

no

Where to look: "desktop", "downloads", "documents", "current", or an absolute/relative path. Omit to search all common locations.

read_document

Reads a .docx file and returns the full text content.

Parameter

Type

Required

Description

path

string

yes

Absolute or relative path to a .docx file

search_document

Searches for text within a .docx file and returns matching lines with context.

Parameter

Type

Required

Description

path

string

yes

Absolute or relative path to a .docx file

query

string

yes

Text to search for (case-insensitive)

get_document_metadata

Returns metadata about a .docx file including name, size, dates, and word/character counts.

Parameter

Type

Required

Description

path

string

yes

Absolute or relative path to a .docx file

list_documents

Lists all .docx files in a directory.

Parameter

Type

Required

Description

directory

string

yes

Absolute or relative path to a directory

Example Usage

Natural language (the point of this whole thing):

  • "Summarize the cloud architecture doc on my desktop"

  • "Search for 'authentication' in the API proposal I downloaded"

  • "What Word documents are in my Downloads?"

  • "Open the RFP and tell me the deadline"

Explicit paths (if you really want to):

  • "Read C:/docs/spec.docx and summarize it"

  • "Search for 'budget' in /Users/me/Documents/report.docx"

Requirements

  • Node.js ≥ 18

  • Works on Windows, macOS, and Linux

License

MIT

Available Tools

5 tools
get_document_metadataA

Returns metadata about a .docx file including file name, size, creation date, modification date, word count, character count, and line count. Use this for document statistics or to verify a document before reading.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute or relative path to a .docx file

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It conveys a read-only intent via 'Returns metadata' and 'verify before reading', but lacks details on error handling, file existence checks, or permissions. This is adequate but not rich.

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?

Two concise sentences, front-loaded with the return value and followed by use cases. No wasted words, every sentence earns its place.

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?

For a simple single-parameter metadata tool with no output schema, the description fully covers what is returned (listing all metadata fields) and when to use it. It is complete for the tool's 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 coverage is 100%, so baseline is 3. The description does not add meaning beyond the schema's 'path' parameter; it only repeats that it applies to .docx files, which is already in the schema. No extra value.

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 the specific verb 'Returns' and resource 'metadata about a .docx file', listing concrete fields (file name, size, dates, counts). This distinguishes it from siblings like read_document (content) or search_document (search).

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

Usage Guidelines4/5

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

Provides clear use cases: 'for document statistics or to verify a document before reading'. This implies when to use over reading, but does not explicitly name alternatives or exclusions, so slightly below a perfect score.

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

list_documentsA

Lists all .docx files in a directory. Use this to discover what Word documents are available in a specific folder. Returns full paths for each .docx file found.

ParametersJSON Schema
NameRequiredDescriptionDefault
directoryYesAbsolute or relative path to a directory

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the return format (full paths) and the specific file type (.docx), which goes beyond the tool name. It implies a read-only listing operation, though it does not explicitly mention limitation such as recursive vs. non-recursive behavior.

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 description is two sentences, front-loaded with the core action, and includes a purpose statement plus a return-value detail. Every word earns its place with no redundancy or filler.

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?

For a simple list tool with one parameter and no output schema, the description is complete: it defines what is listed, why to use it, and what it returns (full paths). There is no ambiguity that would prevent an agent from invoking it correctly.

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% for the single 'directory' parameter, so the baseline is 3. The description adds minimal new meaning beyond the schema, simply restating that the operation occurs within a directory/folder without providing extra syntax or constraints.

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 the verb (Lists), the resource (.docx files), and the scope (a directory). It is distinct from sibling tools like read_document, search_document, get_document_metadata, and resolve_document, focusing on discovery rather than content operations.

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

Usage Guidelines4/5

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

The description provides clear usage context: 'Use this to discover what Word documents are available in a specific folder.' It does not explicitly mention exclusions or name alternative tools, but the context is unambiguous and appropriate for selecting this tool over its siblings.

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

read_documentA

Reads a .docx file and returns the full text content. Use this to read, summarize, or analyze a Word document. Requires an absolute or relative path — use resolve_document first if you only have a document name.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute or relative path to a .docx file

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the tool reads a file and returns the full text content, and notes the path requirement. It doesn't detail error cases or binary handling, but for a simple read operation, the key behaviors are transparently described without contradiction.

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 description is two sentences with no fluff. It front-loads the core action ('Reads a .docx file'), then provides usage and prerequisite context. Every sentence earns its place.

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?

For a single-parameter tool with no output schema, the description is complete: it states the function, the output (full text), the path requirement, and a reference to resolve_document for common scenarios. It is sufficient for an agent to select and invoke the tool correctly.

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 already provides 100% coverage for the single 'path' parameter, describing it as 'Absolute or relative path to a .docx file'. The description adds a pointer to resolve_document for name-only inputs, but this is more usage guidance than parameter semantics. Baseline 3 is appropriate as the description adds marginal value beyond the schema.

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 starts with 'Reads a .docx file and returns the full text content', which is a specific verb and resource, clearly distinguishing it from sibling tools like search_document, get_document_metadata, list_documents, and resolve_document. It also states common use cases ('read, summarize, or analyze a Word document'), reinforcing its purpose.

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 explicitly says 'Use this to read, summarize, or analyze a Word document', providing clear usage guidance. It also gives a practical exclusion: 'use resolve_document first if you only have a document name', naming a specific alternative tool for a prerequisite scenario.

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

resolve_documentA

Finds .docx files by friendly name and optional location. Use this when a user refers to a document by name (e.g., 'the report on my desktop') rather than by full path. Returns the resolved absolute path, a list of candidates if ambiguous, or helpful error if not found. After resolving, use read_document or search_document with the resolved path.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYesFriendly document name, with or without .docx extension (e.g., "report" or "report.docx")
locationNoWhere to look: "desktop", "downloads", "documents", "current", or an absolute/relative path. Omit to search all common locations.

TDQS

A4.5/5.0
Behavior4/5

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

Even without annotations, the description discloses key behavioral outcomes: resolved absolute path, candidate list for ambiguous names, and helpful error for not found. This explains the tool's return behavior and implies a non-destructive read operation. Missing details like case sensitivity or permissions are minor for a resolver.

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 description is three sentences, front-loaded with the core purpose, followed by usage context and output behavior. Every sentence earns its place, and there is no redundancy or filler.

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 tool's moderate complexity and lack of output schema, the description adequately covers return values (path, candidates, error), usage triggers, and downstream integration with sibling tools. It is complete for an agent to select and invoke correctly.

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%, with clear descriptions for both 'name' and 'location'. The description adds contextual examples ('the report on my desktop') and confirms the optional nature of location, but does not substantially extend beyond what the schema already provides.

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 uses a specific verb ('Finds') and resource ('.docx files'), clearly stating the tool resolves friendly names and optional locations to absolute paths. It distinguishes itself from siblings like read_document and search_document by focusing on name-to-path resolution.

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?

Explicitly states when to use: 'when a user refers to a document by name ... rather than by full path.' It also provides a clear follow-up instruction to use read_document or search_document with the resolved path, guiding the agent on alternatives and next steps.

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

search_documentA

Searches for text within a .docx file and returns matching lines with line numbers and context. Case-insensitive. Use for finding specific content within a document.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute or relative path to a .docx file
queryYesText to search for (case-insensitive)

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals key behaviors: the search is case-insensitive, and it returns matching lines with line numbers and context, which is more informative than a generic search description. It does not discuss error handling or edge cases, but for a read-only search tool, the essential behaviors are covered.

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 description consists of three concise sentences, each serving a clear purpose: statement of function, behavioral detail (case-insensitivity), and usage context. There is no redundancy or extraneous information, making it highly efficient.

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?

For a simple two-parameter tool without an output schema, the description is complete. It covers the tool's purpose, return format ('matching lines with line numbers and context'), the case-insensitive behavior, and when to use it. The absence of error details is acceptable for a tool of this simplicity.

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 already provides complete descriptions for both 'path' and 'query', with 100% coverage. The description adds 'case-insensitive' but this is also noted in the schema's query property. Therefore, the description does not add significant meaning beyond what the schema already provides, warranting the baseline score of 3.

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 the tool's function: 'Searches for text within a .docx file and returns matching lines with line numbers and context.' This specifies the operation, resource, and output format, and it distinguishes the tool from siblings like read_document (which likely returns the full document) and get_document_metadata (which provides metadata).

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

Usage Guidelines4/5

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

The description provides explicit usage guidance: 'Use for finding specific content within a document.' This clearly indicates when the tool is appropriate. However, it does not explicitly mention alternatives or contrast with sibling tools, so it falls short of the highest tier of guidance.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 5 tool updatesv1.0.0
    • First observedget_document_metadata
    • First observedlist_documents
    • First observedread_document
    • First observedresolve_document
    • First observedsearch_document
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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: reading full content, searching with context, retrieving metadata, listing files, and resolving paths. There is no meaningful overlap—even list_documents and resolve_document serve different discovery functions.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (read_document, search_document, get_document_metadata, list_documents, resolve_document). The singular/plural distinction is natural and does not break the convention.

Tool Count5/5

Five tools is well within the 3-15 ideal range and covers the core operations needed for a read-only docx server without bloat or sparseness.

Completeness5/5

For the stated purpose of reading, searching, and analyzing Word documents, the tool surface is complete. It covers discovery (list, resolve), access (read), search, and metadata, forming a coherent workflow with no dead ends.

Maintenance

ActivityInactive
ResponsivenessSyncing

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