web2md-mcp

Server Quality Checklist

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

Latest release: v0.8.1
Disambiguation2/5
The three URL conversion tools (convert_url, bridge_convert_url, agent_convert) create significant overlap, especially for Reddit/JS/login-protected pages, where bridge_convert_url and agent_convert seem to serve the same purpose. The descriptions attempt to distinguish them by method, but an agent will struggle to know which to choose. semantic_search and get_conversion are distinct, but the converter cluster muddies the set.
Naming Consistency2/5
Naming conventions are mixed: convert_url and get_conversion follow verb_noun, while semantic_search is a compound noun, and bridge_convert_url, agent_convert, agent_batch_convert use method prefixes (bridge_, agent_) rather than consistent action-first names. This inconsistency makes the tool surface harder to predict.
Tool Count5/5
With 6 tools, the count is well within the ideal range for a focused web-to-markdown server. Each tool has a clear role in the conversion and retrieval workflow, including variations for extension-based conversion and batch processing. No bloat or trivial tools.
Completeness3/5
The core lifecycle is covered: convert, retrieve by ID, and search. However, there is no list-all-conversions tool and no delete/update operation, leaving a notable gap in managing saved conversions. The presence of three overlapping conversion methods partly compensates for missing features but also adds confusion.
Average 3.8/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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
This repository is licensed under MIT License.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that it searches saved conversions and works across languages, but it doesn't disclose the return format, ranking behavior, or any limitations such as authentication or rate limits. This is minimal disclosure for a tool with no annotation support.
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 concise sentences, front-loading the main verb and resource ('Search your saved conversions...') and adding a useful cross-language capability in a short second sentence. There is no wasted text.
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?
The tool is simple with two parameters and no output schema, but the description omits any mention of result format or ordering. It covers the core functionality adequately but misses additional context that would help an agent understand expected outcomes, especially since there are no annotations or output schema to fill the gap.
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 fully describes both parameters: query as 'Natural language search query' and limit as 'Max results (default: 5)'. With 100% schema coverage, the description adds no additional parameter semantics, so the baseline 3 applies.
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 searches saved conversions using natural language, which is a specific verb and resource. The cross-language feature adds a distinguishing detail that separates it from sibling conversion tools like convert_url and get_conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied—searching saved conversions—but there is no explicit guidance on when to prefer this over alternatives like get_conversion, nor any when-not-to-use exclusions. The context from sibling names helps, but the description itself lacks direct usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses the output format (Markdown and metadata) which is helpful, but it does not mention that the tool fetches the webpage over the network, potential delays, or any failure modes. The description is adequate but lacks deeper 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 two sentences, with the primary action front-loaded. It avoids repetition and every phrase adds value: the verb, the resource, the output format, and the specific metadata returned. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 covers the core behavior (conversion to Markdown) and return metadata. It does not explain tool selection among conversion-related siblings, which would improve completeness, but for a simple conversion tool it is mostly adequate.
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 covers all parameters with descriptions (100% coverage), including the URL format and boolean toggles for links and images. The description adds some context by mentioning metadata like 'title, word count, reading time' but does not clarify how 'includeLinks' or 'includeImages' affect the output. Baseline of 3 is appropriate since schema does the heavy lifting.
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 'Convert' with a clear resource ('a webpage URL') and outcome ('to clean Markdown'), and further specifies the return value ('Markdown content and metadata'). It distinguishes itself from sibling tools like 'semantic_search' by clearly stating its conversion purpose, though not explicitly comparing to other conversion tools, it is still specific enough.
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 states what the tool does but gives no guidance on when to use it versus alternatives. With siblings like 'bridge_convert_url', 'agent_convert', and 'agent_batch_convert', there is no mention of selection criteria, prerequisites, or scenarios where this tool is preferred. This is a clear gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are available, so the description carries the full burden. It discloses the read-only nature ('Retrieve') and the return format ('full Markdown content'), but does not mention error behavior, edge cases, or side effects. This is minimally acceptable but lacks depth for a tool without annotation support.
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, concise sentence that front-loads the purpose and includes essential details (full Markdown content, by ID). Every word earns its place, and there is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one required parameter and no output schema, the description adequately conveys the return type and purpose. It does not cover error handling or prerequisites, but given the low complexity and schema coverage, the description is complete enough for selection and invocation.
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 fully describes the only parameter ('id' as 'The conversion ID'), and the description's 'by its ID' is a restatement rather than additional semantic value. With 100% schema coverage, the baseline of 3 applies since the description adds nothing 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 uses a specific verb ('Retrieve') and identifies the resource ('full Markdown content of a previously saved conversion') and the key qualifier ('by its ID'). This clearly distinguishes it from sibling tools that perform conversions or searches rather than retrieving existing conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context ('previously saved conversion') but does not explicitly state when to use this tool versus alternatives or when not to use it. The sibling list shows other tools, but no direct comparisons or exclusions are provided, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It mentions the extension prerequisite and auto-discovery of the extension ID, which is useful. However, it does not disclose what the function returns, error behavior, or side effects, leaving some uncertainty for a conversion tool lacking an output schema.
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 concise sentences, front-loaded with the primary action and immediately clarifying the distinctive extension requirement. Every word earns its place with no fluff or repetition.
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?
Given the simple parameters and no output schema, the description covers the key prerequisites and use cases, but it omits the return format and failure modes. For a conversion tool, the lack of output information is a noticeable gap, making it not fully complete.
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 property descriptions already explain the URL format and extensionId override. The tool description adds redundant mention of auto-discovery but does not provide additional semantic value beyond the schema, matching the baseline for high coverage.
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 'Convert a URL' and the resource 'using your Chrome extension', distinguishing it from sibling convert_url by emphasizing the extension requirement and specific use cases (Reddit, JS-rendered, login-protected pages). This avoids ambiguity with similar tools.
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 explicitly states when this tool is required (Reddit, JS-rendered sites, login-protected pages) and mentions the prerequisite (extension must be installed and running). It does not explicitly exclude alternatives or name them, but the context is clear enough for the agent to select appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses important prerequisites (Chrome running, extension, native host) but omits failure modes, return format, or side effects, leaving gaps in behavioral clarity.
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 main action, and each sentence contributes value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers purpose, prerequisites, and use cases well, but lacks return value details, which would enhance completeness.
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 covers 100% of parameters, so baseline is 3. The description adds no extra meaning beyond the schema's url description, just contextual use cases.
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 converts a URL via Chrome extension and native messaging, and specifies ideal use cases (Reddit, login-protected, JS-rendered), which distinguishes it from sibling convert tools.
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 explicit best-use context and lists requirements, but does not explicitly name alternatives or when-not-to-use cases, so it falls short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds useful context: 'URLs are processed sequentially' (processing order) and 'Requires: Chrome running + Web2MD extension + native host installed' (prerequisites). This goes beyond a bare statement of purpose. However, it does not disclose failure behavior, return values, or potential side effects, which prevents a perfect score.
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 concise and well-structured, consisting of three short sentences that deliver essential information without redundancy. It front-loads the main purpose, then adds context (ideal use cases) and prerequisites. Every sentence earns its place.
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?
The tool has a single parameter with high schema coverage and no output schema, so the description should ideally explain what the tool returns or results in. It does not mention return format or error handling. Given the moderate complexity, some key context is missing, making it adequate but not fully complete.
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 a clear description for the sole parameter 'urls' ('Array of URLs to convert (max 50)'), giving 100% schema description coverage. The description adds only an example of suitable URLs ('many Reddit threads or JS-rendered pages') and notes sequential processing, but these do not significantly enhance parameter understanding. Baseline 3 is appropriate.
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: 'Batch convert multiple URLs using the Chrome extension via native messaging.' It specifies the verb 'convert', the resource (multiple URLs), and the method (Chrome extension/native messaging). It distinguishes from sibling tools by emphasizing 'batch' and 'multiple', making it stand out from single-URL converters like convert_url.
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: 'Ideal for converting many Reddit threads or JS-rendered pages.' This implies when to use the tool (large numbers of URLs or JS-heavy content). It also lists prerequisites ('Chrome running + Web2MD extension + native host installed'), which guide the user on necessary conditions. However, it does not explicitly mention alternatives or cases where this tool should be avoided, so it falls short of a 5.
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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