VibeHacker
Server Details
Product Hunt for AI tools. Search, submit, upvote from Claude Code or Cursor.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- vibe-hacker/vibehacker
- GitHub Stars
- 0
Available Tools
7 toolsget_productGet a toolARead-onlyIdempotentInspect
Get one product by slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as read-only, idempotent, and non-destructive, so the description does not need to repeat safety traits. It adds exact-single-item retrieval by slug, but it does not disclose not-found behavior or response details. Overall, it is consistent with annotations and provides modest behavioral context beyond them.
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 one short sentence with no filler. It states the action, the resource, and the lookup criterion efficiently.
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 low complexity, rich annotations, and single parameter, the description is largely complete for selecting and invoking the tool. It could mention what happens when no product is found, but that is not essential for a simple read-only getter.
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 0%, so the description must clarify the parameter. It does so by identifying the slug as the product lookup key, which meaningfully extends the bare schema definition of a string with minLength 1. For a single-parameter tool, this is sufficient for correct invocation.
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 operation: retrieve one product by slug. It is not a tautology and differentiates from broader tools like search_products, though it does not explicitly distinguish it from preview_product. The resource and lookup mechanism are clear.
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 gives no explicit guidance on when to use this tool versus siblings such as search_products or preview_product. The phrase 'by slug' implies exact-key retrieval, but no alternatives or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesList categoriesARead-onlyIdempotentInspect
List categories with product counts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that results include product counts, which is useful, but it does not disclose ordering, pagination, or return shape. This is modest added value beyond annotations.
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 with no wasted words. It conveys the action and the key output feature efficiently.
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 no-parameter, read-only list operation with rich annotations, the description is nearly complete. It indicates the result includes product counts; only minor details such as response format or sorting are absent, but they are not critical for invoking this simple tool correctly.
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 tool has zero parameters, so the schema fully covers inputs by definition and the baseline is 4. The description adds no parameter-specific meaning, but none is needed.
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 and resource: 'List categories with product counts.' It clearly communicates the operation and the key output, and it is easily distinguishable from the product-focused sibling tools.
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: call when you need categories with product counts. However, it does not explicitly state when to prefer this tool over alternatives or mention any exclusions. With no overlapping siblings, this is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
my_submissionsMy submissionsARead-onlyIdempotentInspect
List the products you submitted and their review status. Requires a token.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds the useful requirement that a token is needed and clarifies the scope as the caller's own submissions, going beyond the annotation-only picture.
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 states the core capability, the resource scope, the output, and the auth requirement without any filler. Every word contributes 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?
For a parameterless read-only tool, the description is complete: it names the resource, the output dimension (review status), and the auth requirement. The rich annotations cover safety, and no output schema exists, but the description sufficiently indicates what the caller will get.
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 tool has zero parameters, and the schema coverage is 100% via an empty properties object. With no parameters to document, the description carries no parameter burden, so the baseline of 4 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 states a specific action ('List'), a resource ('products you submitted'), and the key output ('review status'). This clearly distinguishes it from siblings like search_products or get_product, which target all products or a single product.
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 the tool is for viewing your own submissions and their review status, and notes that a token is required. However, it does not explicitly state when to prefer this over alternatives or provide exclusions, so usage guidance is mostly implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
preview_productPreview a listingARead-onlyIdempotentInspect
Draft a listing for a website without submitting it. Requires a token.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds a meaningful auth-related requirement ('Requires a token') and clarifies that no submission occurs, which aligns with the read-only annotation. No contradictions found.
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 short sentences with no wasted words: the first front-loads the action and scope, and the second adds a necessary precondition. Every sentence 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 one-parameter tool with rich annotations, the definition is mostly adequate, but it lacks any mention of what the tool returns or what a 'preview' actually provides. There is no output schema, so the description should compensate, but it does not describe the result of calling this tool. The token requirement is mentioned but not elaborated.
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 0%, so the description must compensate, but it never explains what 'url' refers to or how it relates to the listing being previewed. The parameter name and format are self-evident, but the description adds no semantic value beyond the schema. It also introduces a token requirement that is absent from the input schema, which could confuse the agent about the expected input.
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 ('draft') and resource ('a listing'), and explicitly contrasts with 'without submitting it', which distinguishes this tool from the sibling submit_product. The title 'Preview a listing' reinforces the action. An agent can tell what this tool does and what it deliberately avoids.
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 'without submitting it' provides clear context that this is a dry-run or preview action rather than a publication action. It implies when to use it, but it does not explicitly name alternatives or state exclusions beyond not submitting. A small but useful gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_productsSearch toolsARead-onlyIdempotentInspect
Search published products by name, tagline, or maker.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| category | No | Category slug from list_categories. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds useful context that only 'published' products are searched and that the search targets name, tagline, or maker. However, it does not disclose behaviors like result ordering, pagination, or query matching semantics beyond the annotations.
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 front-loads the key verb and object, with no filler or redundancy. Every word earns its place, and the structure is ideal for quick agent scanning.
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 search tool with three parameters and no output schema, the description provides the essential purpose but omits return value details, pagination behavior, and whether category is combinable with query. The annotations cover the safety profile, so this is moderately complete but leaves meaningful gaps for an autonomous agent.
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 only 33% (only category is documented). The description partially compensates by clarifying that the query parameter searches across name, tagline, or maker, but it leaves the limit parameter entirely undocumented in both schema and description. This is partial compensation for the coverage gap, not full.
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 ('Search') with a clear resource ('published products') and criteria ('by name, tagline, or maker'). This clearly distinguishes it from sibling tools like get_product (fetch a single product) or list_categories (list categories), making its 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 description gives no guidance on when to use this tool versus alternatives. It does not mention conditions for using get_product to fetch details, list_categories for category navigation, or any exclusions such as 'only use for published products'. Usage must be inferred entirely from the tool name and sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_productSubmit a productAIdempotentInspect
Submit a website to VibeHacker. Reads the site, drafts the listing, and files it for review. Requires a token. If the website was already submitted, returns the existing listing instead of creating a duplicate.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The product's website, e.g. https://example.com | |
| note | No | Optional note for the reviewer (not published). | |
| maker | No | Set true if you built this product. Default true. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare mutation, idempotency, and non-destructiveness; the description adds meaningful context by explaining the pipeline (reads site, drafts listing, files for review), the token requirement, and the dedupe behavior. It aligns with the idempotentHint and adds no contradictions, giving agents a realistic picture of side effects.
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 three sentences with zero filler, front-loading the action and then providing distinct pieces of value: the process, the auth requirement, and duplicate handling. Every sentence 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?
It covers the process, auth, and duplicate behavior, but it does not specify what a successful first-time submission returns—only the duplicate case returns an existing listing. With no output schema present, this is a noticeable gap, and it also doesn't indicate how the required token is supplied.
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 of 3 applies: the schema already documents url, note, and maker thoroughly. The description adds no parameter-specific guidance beyond saying 'website' and 'token', but nothing more is needed because the schema carries that weight.
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 states a specific action—'Submit a website to VibeHacker'—and gives the concrete process: reads the site, drafts the listing, and files it for review. It clearly distinguishes the tool from siblings like get_product or preview_product, and the duplicate-handling clause further defines its scope.
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 intended usage is implied: use this when you want to submit a new website, and it even reassures agents that handling an already-submitted site is safe. However, it never explicitly names alternatives or says when to prefer get_product, preview_product, or upvote_product instead, leaving routing mostly to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
upvote_productUpvote a toolAInspect
Toggle your upvote on a product. Requires a token.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Tool slug, e.g. claude-code |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations mark the operation as non-read-only, non-idempotent, and non-destructive; the description adds that it toggles state, which explains the alternating behavior, and explicitly requires a token (auth context). No contradiction with annotations.
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 short sentences with no redundant language; the action is front-loaded and the auth requirement is stated separately. 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 single-parameter toggle operation, the description plus schema are largely sufficient: purpose, target (slug), and auth requirement are all present. It stops short of describing the response or error behavior, but no output schema exists and the operation is simple.
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 covers the only parameter (slug) with a clear description and example; the tool description adds no additional meaning to the parameter. Baseline 3 applies due to high schema coverage.
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?
Description uses a specific verb ('Toggle') and resource ('your upvote on a product'), which clearly distinguishes from siblings like get_product or submit_product. Even without opening the schema, an agent knows this tool mutates vote state rather than reading or listing.
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 this tool over alternatives. It does not mention that toggling is appropriate for both adding and removing an upvote, nor does it point to get_product or preview_product for read-only viewing. The token requirement is a prerequisite, not a usage guideline.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
10 tool updates
- Added
get_product - Removed
get_tool - Added
preview_product - Removed
preview_tool - Added
search_products - Removed
search_tools - Added
submit_product - Removed
submit_tool - Added
upvote_product - Removed
upvote_tool
7 tool updates
- First observed
get_tool - First observed
list_categories - First observed
my_submissions - First observed
preview_tool - First observed
search_tools - First observed
submit_tool - First observed
upvote_tool
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
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.
Discussions
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TDQS
Most tools target distinct actions or resources, but preview_product and submit_product overlap since submit_product also drafts the listing before filing it. The descriptions are enough to tell them apart, though an agent could briefly confuse them.
Tool names mostly follow a clear verb_noun snake_case pattern: get_product, list_categories, search_products, submit_product, upvote_product. The main deviation is my_submissions, which uses a possessive noun phrase instead of an action verb.
Seven tools is a well-scoped set for a product submission and voting directory. Each tool serves a meaningful part of the workflow without unnecessary redundancy or bloat.
The core workflow is covered: browsing categories, searching products, viewing a product, previewing and submitting listings, checking submission status, and upvoting. Minor gaps exist such as no update or delete for submissions, but these do not severely block the primary use case.