blog
Server Details
Cloudflare Workers MCP server: blog
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- lazymac2x/blog-api
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.5/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: listing all articles, retrieving a specific article by slug, and full-text searching. No functional overlap.
All tool names follow a consistent verb_noun pattern using snake_case (get_article, list_articles, search_articles), making them predictable.
Three tools is appropriate for a read-only blog server, covering the essential operations of listing, retrieving, and searching without unnecessary bloat.
The server is limited to read-only operations (list, get, search). It lacks CRUD operations like create, update, and delete articles, which are common for blog management, leaving significant gaps.
Available Tools
3 toolsget_articleBInspect
Get the full Markdown body of a specific blog article by slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Article slug, e.g. mcp-server-security-top-10-vulnerabilities-2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden for behavioral disclosure. It confirms read-only operation but omits details on error handling (e.g., missing slug), authentication requirements, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 12 words, no redundancy, front-loaded with essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema), the description covers what it returns (Markdown body) and how to identify the article (by slug). Minor gap: behavior when slug is invalid or missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the 'slug' parameter is already described). The description adds 'by slug' but provides no additional semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'full Markdown body of a specific blog article', and the identifier 'by slug', effectively distinguishing it from sibling tools list_articles and search_articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 (list_articles, search_articles), no prerequisites, and no conditions for proper use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_articlesAInspect
List all blog articles with slug, title, description, date, tags, and reading time.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Filter by tag (optional) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided; the description should disclose behavioral traits. It does not mention pagination, ordering, rate limits, or any side effects, which are important for a list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys purpose and output fields without waste. It earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description lists return fields, which is helpful. However, it lacks information on pagination and ordering, which are typical for list endpoints. Sibling tools exist but no differentiation is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'tag' parameter described. The description does not add extra semantics beyond what is in the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and resource 'blog articles', and specifies the fields returned. It implicitly distinguishes from siblings 'get_article' (single article) and 'search_articles' (searching).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for listing all articles, but does not provide explicit guidance on when to use this tool versus 'get_article' or 'search_articles', nor does it mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_articlesAInspect
Full-text search across article titles, descriptions, tags, and bodies. Returns matching articles with a relevance score.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search terms |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions returns relevance scores but does not discuss pagination, sorting, constraints, or safety of operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no extraneous words, front-loaded with key action and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Low complexity with one param and no output schema; description adequately explains functionality but could mention result limits or ordering.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with query described as 'Search terms'. Description adds value by specifying fields searched (titles, descriptions, tags, bodies) beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies a full-text search across multiple fields (titles, descriptions, tags, bodies) and mentions returning relevance scores, distinguishing it from siblings like get_article and list_articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use search_articles versus siblings. Does not specify alternatives for browsing vs searching or retrieving specific articles.
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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{
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