Marketing Skills Directory
Server Details
Search, browse & read 340+ Claude Code marketing & SEO skills from any MCP client.
- Status
- Healthy
- Last Tested
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- Streamable HTTP
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.9/5 across 7 of 7 tools scored.
Each tool has a clearly distinct purpose: retrieving sets, individual skills, categories, sets, browsing, recommendation, and search. No overlap in functionality.
All tool names follow a verb_noun pattern. Minor inconsistency: 'get' uses singular nouns while 'list' uses plural nouns, but the pattern is still clear and predictable.
With 7 tools, the server is well-scoped for a skills directory covering listing, searching, recommending, and detail retrieval. Nothing feels excessive or insufficient.
The tool surface covers all essential operations for a directory: browsing categories, listing sets, searching, recommending, and retrieving details. No obvious dead ends, though total coverage is not exhaustive (e.g., no random skill tool).
Available Tools
7 toolsget_setGet skill setAInspect
Return a skill set with full details for each contained skill.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Set slug, e.g. "video-production-suite". |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It indicates the tool returns data ('full details') but does not mention any side effects, performance characteristics, or access restrictions. For a simple get operation, this is adequate but not exemplary.
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 sentence of 11 words, front-loaded with the action and resource, and contains no filler. Every word 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?
For a simple tool with one parameter and no output schema, the description is largely sufficient. It explains what the tool returns. However, it could mention how this differs from 'list_sets' and what exactly 'full details' entails. Still, it is complete enough for most use cases.
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?
The input schema has 100% coverage with a description for the 'slug' parameter. The tool description adds no additional meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 action ('Return'), the resource ('a skill set'), and the scope ('with full details for each contained skill'). It distinguishes from sibling tools like 'get_skill' (which returns a single skill) and 'list_sets' (which likely lists sets without full details).
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 when a user wants detailed information about a specific skill set, but it does not explicitly state when to use this tool versus alternatives, nor does it provide when-not-to-use guidance. Sibling tools are listed but not compared.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_skillGet skill contentAInspect
Return the full SKILL.md content for a skill by slug. Free skills return content; premium skills return a purchase URL unless a valid access code is supplied.
| Name | Required | Description | Default |
|---|---|---|---|
| code | No | Optional access code to unlock a premium skill. | |
| slug | Yes | Skill slug, e.g. "cold-email". |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully explains the conditional behavior: free skills return content, premium skills return a purchase URL unless a valid access code is provided. It does not mention idempotency or side effects, but the read-only nature is clear.
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?
Two sentences with no wasted words, front-loaded with the primary purpose, and efficiently conveys all necessary 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?
No output schema is provided, but the description sufficiently explains what is returned for both free and premium skills, covering all return scenarios. The tool is simple and the description is complete.
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?
The schema covers both parameters, but the description adds value by explaining that the 'code' parameter unlocks premium skill content, providing context beyond the schema's description.
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 tool returns the full SKILL.md content for a skill by slug, and distinguishes between free and premium skill behavior, which differentiates it from sibling tools like list_skills or search_skills.
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 context (for retrieving a specific skill's content) but does not explicitly state when to use this tool versus alternatives, nor does it provide any 'when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesList categoriesAInspect
List all skill categories with counts (the filter vocabulary for list_skills).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It reveals the tool lists all categories with counts, which is helpful but does not specify read-only nature or other behaviors. It is clear and non-contradictory.
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?
A single sentence that is front-loaded with key information: what it lists, that counts are included, and its purpose as filter vocabulary. No wasted words.
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?
For a zero-parameter tool with no output schema, the description covers purpose and output content (categories with counts). It could mention the output structure in more detail, but given simplicity, it is largely complete.
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?
There are no parameters, and schema coverage is 100%. The description adds value beyond the schema by noting the output includes counts and the relationship to list_skills, which compensates for lack of param info.
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 'List all skill categories with counts' and explicitly connects it to 'the filter vocabulary for list_skills', distinguishing it from sibling tools like list_skills.
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 as the filter vocabulary for list_skills, offering context on when to use. It does not explicitly state when not to use, but with no parameters and clear purpose, it is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_setsList skill setsBInspect
List curated skill sets (bundles) with their skill slugs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It fails to mention if the tool is read-only, whether returns all sets or paginated, or any other safety or performance characteristics.
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 with no wasted words; front-loaded with the verb 'List' and concise description of what is listed.
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?
For a simple list tool with no parameters and no output schema, the description is reasonably complete, stating the content (curated skill sets with skill slugs). Could mention that it returns all sets, but still adequate.
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% (zero parameters), so baseline 3. Description adds no further param info, which is acceptable given no parameters.
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?
Clearly states the action 'list' and resource 'curated skill sets (bundles)', and specifies they include 'skill slugs', distinguishing it from siblings like 'get_set' (single set) and 'list_skills' (individual skills).
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 explicit guidance on when to use this tool versus alternatives; lacks context about when 'list_sets' is preferred over 'get_set' or 'search_skills'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_skillsList / browse skillsAInspect
Browse the catalog, optionally filtered by category. Paginated.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No | ||
| category | No | Filter by category name (see list_categories). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions pagination and optional category filter but does not disclose ordering, default behavior, rate limits, or side effects. Basic but not deep 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded, no redundancy. Every sentence adds value.
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?
Moderate complexity; description covers core functionality. Lacks return format details (since no output schema), but for a simple browse tool it is reasonably complete.
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?
Adds meaning for category parameter by referencing list_categories for valid values. Mentions pagination implicitly for limit/offset. Schema coverage is 33%, so description adds value 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 it browses the catalog with optional category filter and pagination. The name and title reinforce this. It distinguishes from siblings like search_skills (browse vs search) and list_categories (different entity).
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 explicit guidance on when to use this versus alternatives like search_skills or recommend_skill. Implicitly for browsing unfiltered or by category, but lacks exclusions or when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recommend_skillRecommend a skill for a taskAInspect
Given a natural-language task, return the top 3 matching skills with the exact install command.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | What you want to do, e.g. "write a cold outreach email sequence". |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses returning top 3 matching skills and install command, but does not mention failure modes, ranking method, or platform specificity. Adequate but gaps remain.
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 clear sentence with no wasted words. Front-loaded with key 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 no output schema, description explains return value (top 3 skills with install command). Simple tool with one parameter, description covers main behavior adequately. Minor lack of error handling details.
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%, so baseline is 3. The description adds no extra meaning beyond the schema; it only paraphrases the schema's description.
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 tool's purpose: given a natural-language task, return top 3 matching skills with exact install command. It distinguishes from sibling tools like search_skills by specifying top 3 and install command.
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 vs alternatives (e.g., search_skills, list_skills). The description implies usage when task is natural-language, but lacks explicit exclusions or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_skillsSearch skillsAInspect
Full-text (BM25) search over the skills directory. Returns ranked matches with slug, title, description, categories and price.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | Search terms, e.g. "cold email sequence". |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description discloses it is read-only search using BM25 and returns specific fields, but does not mention rate limits, auth requirements, or pagination behavior beyond the limit parameter.
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 wasted words, front-loads the search type and output. Highly concise and structured.
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?
No output schema, but description lists return fields. For a search tool, it covers search algorithm and result format sufficiently given the tool's complexity.
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?
The schema describes query with an example and limit with constraints. The description adds context that it's BM25 search and lists return fields. With 50% schema coverage, this is adequate but not exceptional.
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 it performs full-text (BM25) search over skills, returning ranked matches with specific fields. This distinguishes it from siblings like list_skills (list all) and recommend_skill (recommendations).
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 searching by query terms but does not explicitly state when to use this over list_skills or recommend_skill. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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