VibeMarketing (https://vibemarketing.ninja/mcp) is a directory service that catalogs and provides information about various MCP (Model Context Protocol) servers. It serves as a centralized resource where users can discover different MCP servers and their capabilities. Examples of servers listed in the directory include Sequential Thinking MCP (for dynamic problem-solving through structured thought sequences) and Memory MCP (a knowledge graph-based persistent memory system).
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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.
Average 3.5/5 across 7 of 7 tools scored. Lowest: 2.8/5.
Each tool has a clearly distinct purpose: scheduling (single vs batch), deleting, updating, listing posts, listing accounts, and checking subscription status. The only similar tools, schedule_post and bulk_schedule_posts, are explicitly differentiated by batch size, eliminating confusion.
All tool names follow a consistent verb_noun pattern with lowercase and underscores, e.g., schedule_post, get_all_posts, delete_post. The verbs (schedule, get, delete, update, bulk_schedule) are clear and the nouns are specific, making the naming predictable and readable.
Seven tools is an appropriate scope for a social media marketing server focused on post scheduling. Each tool covers a necessary operation without redundancy or bloat, fitting well within the ideal 3-15 tool range.
The server covers the full lifecycle of scheduled posts: create (schedule_post, bulk_schedule_posts), read (get_all_posts), update (update_post), and delete (delete_post). It also provides account and subscription information. Minor gaps exist, such as no single-post retrieval or account management, but these are not critical for the core scheduling workflow.
bulk_schedule_postsAInspectSchedule multiple social media posts at once (up to 50 posts per batch). More efficient than scheduling posts individually.
| Name | Required | Description | Default |
|---|---|---|---|
| posts | Yes | Array of posts to schedule |
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 of behavioral disclosure. It discloses the batch size limit (up to 50), which is helpful, but does not mention what happens on partial failures, whether the operation is atomic, or any authentication/validation details. This leaves significant behavioral gaps for a bulk mutation tool.
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 two sentences, front-loaded with the primary action, and every word contributes value. It states the function, the batch limit, and the efficiency benefit without any fluff or redundancy.
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?
While the schema is rich and the description covers the core capability, there is no output schema and no mention of return values or error handling. For a bulk operation that can partially fail, the absence of information about partial success or response format leaves the description incomplete in a practical sense.
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%, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema, only restating the batch limit already present in maxItems. It does not clarify nuances like the relationship between posts or any conditional requirements.
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 schedules multiple posts at once, differentiating it from the sibling 'schedule_post' which schedules individually. The specific verb 'schedule' and resource 'multiple social media posts' make the purpose unambiguous.
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 phrase 'up to 50 posts per batch' and 'more efficient than scheduling posts individually' gives clear context for when to use this tool over the singular scheduling option. However, it stops short of explicitly stating 'use schedule_post for a single post' or outlining exclusion criteria, so it earns a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_postAInspectDelete a scheduled post (cannot delete published posts)
| Name | Required | Description | Default |
|---|---|---|---|
| postId | Yes | ID of the post to delete | |
| platform | Yes | Platform the post is on |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool operates on scheduled posts and not published ones, but omits other behavioral traits such as irreversibility, required permissions, or error handling. This is partial disclosure 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the action and the key constraint in a parenthetical. No wasted words, every phrase 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 delete tool with no output schema, the description covers the primary purpose and limitation. However, it does not mention success/error behavior, which would improve completeness, but the core functionality is adequately specified.
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 clear descriptions for both postId and platform. The tool description adds no additional parameter context, so the baseline of 3 applies as the schema already handles semantics.
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 identifies the action (delete) and specific resource (scheduled post), and distinguishes itself from siblings by stating it cannot delete published posts. This gives a precise scope that differentiates it from update_post and schedule_post.
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?
It provides clear context on when to use the tool (for scheduled posts) and an explicit exclusion (published posts). However, it does not explicitly name alternative tools for published posts, though none appear in the sibling list, making the guidance adequate but not exhaustive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_accountsBInspectGet all connected social media accounts across all platforms
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of accounts to return per platform | |
| platform | No | Filter by platform or get all platforms | all |
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 does not disclose behavioral traits such as pagination, rate limits, authentication requirements, or return format. Additionally, saying 'all' conflicts with the schema's 'limit' parameter (default 10), which limits results per platform.
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, concise sentence that directly states the tool's purpose without extraneous information. It is front-loaded and easy to parse.
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 simple nature of the tool (two optional parameters, no output schema) and full schema coverage, the description is minimally sufficient. However, the lack of annotation and output schema means it does not explain what the return value looks like or that 'all' accounts are limited by the 'limit' parameter, leaving room for ambiguity.
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%, so the baseline is 3. The description adds no extra meaning beyond the schema; the phrase 'across all platforms' aligns with the 'platform' parameter but does not clarify the 'limit' parameter's behavior or the meaning of 'connected accounts.'
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 retrieves all connected social media accounts across all platforms, using a specific verb ('Get') and resource ('accounts'). It distinguishes itself from sibling tools like get_all_posts by focusing on accounts, not posts.
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, nor does it mention exclusions or context. It simply states what the tool does without explaining its role relative to siblings like get_all_posts or schedule_post.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_all_postsBInspectGet all posts across all platforms
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of posts to return | |
| status | No | Filter by post status (use "any" to get all statuses) | |
| platform | No | Filter by platform or get all platforms | all |
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. The one-sentence description only restates the purpose and does not mention whether the operation is read-only, requires authentication, has rate limits, or specifies response format.
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, concise sentence that is front-loaded with the verb and resource. It contains no unnecessary words, though it is minimal and lacks broader context.
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 provided, the description should explain return behavior, but it only states the operation without specifying response shape, pagination, or filtering semantics. The schema covers parameter details, but the overall behavior remains incomplete.
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 provides 100% coverage for all three parameters (limit, status, platform) with clear descriptions. The tool description adds no additional parameter semantics beyond the schema, so the baseline score of 3 is justified.
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 retrieves all posts across all platforms, using the specific verb 'Get' and identifying the resource ('posts') and scope. This distinguishes it from sibling tools that schedule, delete, or manage accounts.
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?
There is no guidance on when to use this tool versus alternatives like schedule_post or delete_post. The description does not mention context, prerequisites, or exclusions, leaving the agent to 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.
get_subscription_statusAInspectGet current subscription status and usage
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for disclosing behavior, but it only states the action without elaborating on side effects, return format, or error conditions. Although 'get' implies read-only, it does not explicitly confirm that the tool has no mutations or rate-limit implications.
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, concise sentence that gets directly to the point. No unnecessary words or redundancy.
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 simplicity of the tool (no parameters, no output schema), the description is adequate but lacks details about what 'status' and 'usage' include. It does not specify the response structure, which is the only missing context for a tool of this 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?
There are zero parameters, so the schema fully covers any potential usage. According to the baseline for 0 params, a score of 4 is appropriate even without parameter-level 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 identifies the action ('Get') and the resource ('current subscription status and usage'), which distinguishes it from sibling tools focused on posts and accounts. It is specific and unambiguous.
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 is provided on when to use this tool versus other tools. There is no mention of prerequisites, alternatives, or context, leaving the agent without use-case differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
schedule_postCInspectSchedule a new social media post
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | Post content | |
| platform | Yes | Social media platform | |
| accountId | Yes | Account ID to post from | |
| mediaUrls | No | Optional media URLs | |
| scheduledFor | Yes | When to publish the post |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of disclosing side effects. It does not mention authorization requirements, whether the post is immediately visible or queued, reversibility, or what happens after scheduling. This is a significant gap for a mutation tool.
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 concise sentence with no wasted words. However, it sacrifices informative content for brevity, lacking any details beyond the basic action. It is efficient but not fully earning its place given the tool's complexity.
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 that this is a scheduling/mutation tool with no annotations and no output schema, the description omits critical context such as scheduling constraints, permission requirements, or expected return value. The schema covers parameters but not the operational context. The bare description is inadequate for a tool with 5 parameters and side effects.
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 each parameter having a clear description (e.g., 'When to publish the post'). The tool description adds no parameter-specific meaning, so the schema's descriptions carry the load. Baseline 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 uses the verb 'schedule' with the resource 'social media post', clearly indicating a single-post scheduling action. The word 'new' differentiates it from update_post, and the singular 'a' contrasts with bulk_schedule_posts. However, it doesn't explicitly name alternatives, so slightly less than perfect.
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 is provided on when to use this tool versus bulk_schedule_posts or how it fits into the workflow. The description simply states the action without context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_postAInspectUpdate a scheduled post (cannot update published posts)
| Name | Required | Description | Default |
|---|---|---|---|
| postId | Yes | ID of the post to update | |
| content | No | New content for the post (optional) | |
| platform | Yes | Platform the post is on | |
| mediaUrls | No | New media URLs (optional) | |
| scheduledFor | No | New scheduled time in ISO 8601 format (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses one behavioral limitation (cannot update published posts) but omits other key traits like whether the update is partial or full, permission requirements, or what happens to omitted optional fields. This is insufficient for a mutation tool.
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 that is direct, front-loaded with the action, and includes necessary constraint context. No filler or redundant 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?
The tool has five parameters, no output schema, and no annotations. The description is sparse and does not explain update semantics (e.g., whether omitted optional fields are preserved or cleared), nor does it address prerequisites. The schema helps but the overall behavior remains ambiguous for a mutation tool.
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 provides 100% description coverage for all five parameters with clear definitions (e.g., 'New content for the post (optional)'). The description itself adds no parameter-level detail, but with high schema coverage, a baseline 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 uses a specific verb 'Update' and resource 'a scheduled post', clearly stating the tool's scope. The parenthetical '(cannot update published posts)' distinguishes it from potential sibling tools and prevents misuse.
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?
It provides an explicit when-not condition by stating 'cannot update published posts', which guides the agent to use it only for scheduled posts. However, it doesn't name alternatives or offer guidance on when to use this versus schedule_post or delete_post.
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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{
"$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.
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