Word Document Reader MCP Server

by little2512

Overview Schema Related Servers Score Discussions

JavaScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but there is some potential overlap between 'clear_cache' and 'clear_memory' as both involve clearing operations, which could cause confusion without clear context in their descriptions. The other tools like 'read_word_document', 'search_documents', and document listing/storage tools are well-differentiated.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with clear verb_noun structures (e.g., 'clear_cache', 'get_stored_document', 'list_stored_documents'), making them predictable and easy to understand. There are no deviations in naming conventions.
Tool Count5/5
With 7 tools, the server is well-scoped for a Word Document Reader, covering core operations like reading, searching, listing, storing, and cache management. Each tool appears to serve a specific and necessary function without being overly sparse or bloated.
Completeness4/5
The tool set covers key document handling workflows, including reading, searching, listing, and storage, with added cache management. A minor gap exists in document modification or deletion tools, but the core functionality for a reader is largely complete, allowing agents to perform essential tasks effectively.
Average 2.8/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves content but doesn't describe what happens if the document doesn't exist (e.g., errors), whether it requires authentication, rate limits, or the format of returned content. For a read operation with zero annotation coverage, this leaves significant gaps in understanding behavior.
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, efficient sentence in Chinese that directly states the tool's purpose. It's appropriately sized and front-loaded with the core action. There's no wasted text, though it could be slightly more informative 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 tool has no annotations and no output schema, the description is incomplete. It doesn't explain what 'stored' means in context (e.g., from a cache or database), what content is returned (e.g., text, binary), or error handling. For a tool with one parameter but rich behavioral unknowns, this minimal description is inadequate.
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 schema description coverage is 100%, with the single parameter 'memoryKey' documented as '要获取的文档内存键名' (the memory key name of the document to retrieve). The description doesn't add any meaning beyond this, such as explaining what a 'memoryKey' represents or providing examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose as '获取已存储的文档内容' (get stored document content), which clearly indicates it retrieves document content. However, it doesn't distinguish this from sibling tools like 'list_stored_documents' (which likely lists metadata) or 'read_word_document' (which may read from a different source). The verb+resource is clear but lacks sibling differentiation.
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. It doesn't mention prerequisites (e.g., needing a stored document), exclusions, or comparisons to siblings like 'search_documents' or 'read_word_document'. Without such context, the agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'full-text index search' and language support, but lacks critical behavioral details: it doesn't disclose whether this is a read-only operation, how results are returned (e.g., pagination, sorting), performance characteristics, or error handling. For a search tool with no annotations, this is inadequate.
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 very concise with a single sentence, which is efficient. However, it's under-specified rather than optimally concise—it could benefit from slightly more detail without becoming verbose. It's front-loaded but lacks depth.
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 complexity of a search tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., search results format), how to interpret outputs, or any limitations. This leaves significant gaps for an AI agent to use the tool effectively.
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 description adds no parameter semantics beyond what the input schema provides. The schema has 100% description coverage, clearly documenting 'query', 'documentType', and 'limit' with enums and defaults. The description doesn't explain parameter interactions or provide additional context, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool performs 'full-text index search' and supports 'Chinese-English mixed search', which provides a basic purpose. However, it doesn't specify what resource is being searched (documents, files, etc.) or distinguish it from sibling tools like 'list_stored_documents' or 'get_stored_document'. The purpose is somewhat vague about scope.
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. It doesn't mention when to prefer this over 'list_stored_documents' (which might list without search) or 'get_stored_document' (which retrieves a specific document), nor does it specify any prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. '清空所有缓存' implies a destructive operation that removes cached data, but it doesn't specify what types of data are affected, whether this requires special permissions, if the operation is reversible, what side effects might occur, or what happens after execution. For a potentially destructive tool, this is insufficient 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - just four Chinese characters that directly convey the core function. There's zero wasted language or unnecessary elaboration. It's front-loaded with the essential information in the most compact form possible.
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 cache-clearing operation with no annotations and no output schema, the description is incomplete. It doesn't address important contextual questions: What does 'cache' refer to in this system? What are the consequences of clearing it? Are there different cache types? What confirmation or result should be expected? The single sentence leaves too many practical questions unanswered.
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 description mentions 'all cache' which implies comprehensive clearing, but the input schema shows a 'type' parameter with three options (all, document, index). The description doesn't explain these options or their differences. With 100% schema description coverage, the baseline is 3, but the description adds minimal value beyond what's already in the schema.
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 '清空所有缓存' (Clear all cache) clearly states the action (clear) and target (cache), making the purpose immediately understandable. It doesn't specifically distinguish from sibling tools like 'clear_memory' or 'get_cache_stats', but the verb+resource combination is unambiguous for what this tool does.
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. There's no mention of when this operation is appropriate, what prerequisites might exist, or how it differs from sibling tools like 'clear_memory' or 'get_cache_stats'. The user must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. '清除' (clear) implies a destructive operation, but the description doesn't specify whether this is reversible, what permissions are required, whether it affects system performance, or what happens when memoryKey is omitted. The description mentions the optional parameter behavior but lacks critical 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single Chinese phrase that directly states the tool's function. There's zero wasted language, and it's front-loaded with the core action. This is appropriate conciseness for a simple tool.
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 destructive tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'memory' means in this context, what gets cleared, whether the operation is safe/reversible, what happens when all memory is cleared, or what the tool returns. Given the complexity of a memory-clearing operation, more context is needed.
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?
The description implies parameter semantics by mentioning '指定的' (specified), which aligns with the optional memoryKey parameter. With 100% schema description coverage and only one parameter, the description adds minimal but appropriate context about the parameter's purpose without duplicating schema information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description '清除指定的内存内容' (Clear specified memory content) states the verb (clear) and resource (memory content), but it's vague about what 'memory content' means in this context. It doesn't distinguish this tool from sibling tools like 'clear_cache' or explain what type of memory is being cleared.
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 like 'clear_cache' or other sibling tools. There's no mention of prerequisites, typical use cases, or when this tool would be preferred over other memory/cache management tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions listing documents but doesn't describe pagination behavior, rate limits, authentication requirements, or what 'stored' means in this context. The description is too minimal to adequately inform the agent about how this tool behaves.
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 a single, efficient sentence that gets straight to the point with zero wasted words. It's perfectly concise and front-loaded with the core functionality.
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 list operation with no annotations and no output schema, the description is insufficient. It doesn't explain what information is returned about each document, whether results are paginated, or how 'documentType' filtering affects the output. The agent would need to guess about the tool's behavior and output format.
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 schema has 100% description coverage with a well-documented enum parameter. The description doesn't add any parameter information beyond what's in the schema, but since the schema already fully documents the single optional parameter, the baseline score of 3 is appropriate.
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 '列出所有已存储的文档' (List all stored documents) clearly states the verb (list) and resource (stored documents). It's specific about scope ('all'), but doesn't differentiate from sibling tools like 'search_documents' or 'get_stored_document', which prevents a perfect score.
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 like 'search_documents' (for filtered searches) or 'get_stored_document' (for retrieving a single document). It simply states what the tool does without context about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'cache optimization' but doesn't explain caching behavior (e.g., cache duration, invalidation). It doesn't disclose performance characteristics, error handling, or what 'enhanced' means operationally. The description adds some context about extraction capabilities but leaves critical behavioral traits unspecified.
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, efficient sentence that front-loads the core purpose ('enhanced Word document reader') followed by key features. Every phrase adds value, though it could be slightly more structured by separating core function from optional capabilities.
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 tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (document content? structured data? metadata?), how extracted tables/images are formatted, or what 'memoryKey' storage enables. The agent lacks critical information about the tool's outputs and behavioral guarantees.
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%, so the schema already documents all 7 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters (e.g., how 'extractImages' interacts with 'outputDir') or provide usage examples. Baseline 3 is appropriate when schema does the heavy lifting.
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's function as an 'enhanced Word document reader' with specific capabilities (table extraction, image OCR analysis, cache optimization). It distinguishes itself from basic readers by mentioning these advanced features, though it doesn't explicitly differentiate from sibling tools like 'get_stored_document' or 'search_documents' which might have overlapping functionality.
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. It doesn't mention when this enhanced reader is preferable over simpler tools, nor does it reference any sibling tools for comparison. The agent must infer usage from the feature list alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the action ('get') but doesn't add any context about what the statistics include, whether it's a read-only operation, performance implications, or rate limits. This leaves significant gaps for a tool that likely provides system-level data.
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 a single, efficient sentence in Chinese ('获取缓存统计信息') that directly states the purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the cache statistics include (e.g., hit rates, memory usage), the format of the return value, or any behavioral traits. For a tool that likely provides detailed system data, this leaves too much unspecified.
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?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to add parameter details, and it correctly implies no inputs are required, earning a high baseline score.
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 '获取缓存统计信息' (Get cache statistics) clearly states the verb 'get' and the resource 'cache statistics', providing a specific purpose. However, it doesn't differentiate from sibling tools like 'clear_cache' or 'get_stored_document', which prevents a perfect score.
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 like 'clear_cache' or 'get_stored_document'. There's no mention of context, prerequisites, or exclusions, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![word-doc-mcp MCP server](https://glama.ai/mcp/servers/little2512/word-doc-mcp/badges/card.svg)](https://glama.ai/mcp/servers/little2512/word-doc-mcp)

Score Badge

Copy to your README.md:

[![word-doc-mcp MCP server](https://glama.ai/mcp/servers/little2512/word-doc-mcp/badges/score.svg)](https://glama.ai/mcp/servers/little2512/word-doc-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/little2512/word-doc-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server