PostLaunchKit
Server Details
Search reviewed free tools, submit for review, run launch checks, and find launch directories.
- Status
- Healthy
- Uptime
- 100.0% over 22 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-06-18
- URL
- Repository
- teamhandyapps-oss/postlaunchkit-mcp
- GitHub Stars
- 0
TDQS
Scored across 6 tools
Each tool has a fairly distinct purpose: fetching one entry, searching, categorizing, submitting, listing external launch directories, and running a website check. The only mild overlap is between get_project (directory entries) and list_launch_directories (external dataset), which could confuse an agent about which 'directory' is meant, but descriptions clarify.
All six tools follow a consistent snake_case verb_noun pattern (get_, list_, run_, search_, submit_). No mixed conventions or vague verbs.
Six tools is well-scoped for a small launch-directory and website-check service; each tool covers a distinct operation without redundancy.
Core workflows are covered: discovery (search_projects, get_project, list_categories), submission (submit_project), and external guidance (list_launch_directories, run_launch_check). Minor gaps exist, such as no way to fetch a single launch-directory entry's details or check submission status, but agents can work around these.
Available Tools
6 toolsget_projectBInspect
Get one published directory entry by its slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations the description carries the full burden, and it does disclose one non-obvious behavioral trait: only 'published' entries are returned, so unpublished slugs presumably fail. It says nothing about not-found behavior, permissions, or return shape, so it is only partially transparent.
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 front-loaded sentence with the resource and the lookup key; every word earns its place and nothing is padded.
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 trivial one-param read tool with no output schema this is close to adequate, but the 'published' restriction raises an unanswered question about what happens for unpublished or missing slugs, which an agent calling this tool will need to handle.
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?
One parameter at 0% schema description coverage; the schema only says it is a string. The description adds that the slug is the lookup key for a published entry, which is real semantic value, but gives no format, casing, or uniqueness details.
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?
States a specific verb (get) and resource (one published directory entry) and narrows it with 'by its slug,' which separates it from list_categories and search_projects. It never explicitly names those siblings, but the single-item-by-key framing is 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 when-to-use guidance and no comparison to alternatives such as search_projects for lookup by other criteria. The only implied usage is 'you already have a slug,' which the agent must infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_categoriesAInspect
List directory categories with the number of published entries in each.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose one meaningful behavioral trait — the counts cover only published entries, not all entries — which is genuine added context. However, it says nothing about pagination, result ordering, or whether the operation is a safe read.
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 with the verb front-loaded and the most informative qualifier (published-entry counts) immediately after. Nothing is wasted and nothing is buried.
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 read-only listing with no output schema, the description covers what the tool returns (categories plus per-category counts) and the count scope. The only minor gap is the shape/ordering of the returned list, which is low-stakes here.
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 takes zero parameters, so the schema has nothing to document and the baseline of 4 applies. No additional parameter meaning is needed or expected.
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?
States a specific verb and resource ('List directory categories') and adds scope detail ('with the number of published entries in each'), so the agent knows exactly what comes back. It does not explicitly differentiate itself from the sibling project tools, but those operate on a different resource, so confusion is unlikely.
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 explicit when-to-use or when-not-to-use statement, and no alternative is named. Usage is only implied by the verb 'List' and the fact that none of the siblings (get_project, search_projects, submit_project) cover categories, so the agent can infer this is the sole category-enumeration path.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_launch_directoriesAInspect
List directories and listing sites where an indie product can be submitted, from the open launch-directories dataset (CC BY 4.0). Rows include public eligibility, reciprocity, free-tier conditions, field-specific sources and checked dates. Use checked=true for source-backed options. Provider claims are not independently observed listing links. Blank/unknown stays unknown. Run run_launch_check on the product site before submitting.
| Name | Required | Description | Default |
|---|---|---|---|
| free | No | Only directories with a free option. | |
| query | No | ||
| checked | No | Only source-backed eligibility and free-tier options; not guaranteed approval. | |
| dofollow | No | Only directories whose link is dofollow or dofollow with a badge. | |
| link_type | No | ||
| product_type | No | Public product class, such as software, digital_product or website. | |
| link_evidence | No | ||
| requires_account | No | ||
| ai_agent_friendly | No | ||
| badge_requirement | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does real work: it discloses row contents, warns that 'Provider claims are not independently observed listing links,' and states that 'Blank/unknown stays unknown' rather than being inferred. It omits return shape, result volume, and pagination behavior for a 10-param listing 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?
Purpose and dataset are front-loaded in the first sentence, and the subsequent sentences are substantive caveats rather than filler. It is slightly dense and run-on (mixing row content, evidence caveats, and workflow advice), but almost every clause 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 10-parameter tool with no output schema and no annotations, the description covers data caveats and one recommended filter but leaves much of the filtering surface and the return shape unexplained. It is adequate to call the tool, but not complete enough to predict results.
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 only 40% across 10 params, so the description must compensate, and it partially does: it explains checked=true ('source-backed eligibility and free-tier options; not guaranteed approval') and the reliability semantics behind link_evidence values such as provider_claim and unknown. However, eight other filters (query, free, dofollow, link_type, product_type, requires_account, ai_agent_friendly, badge_requirement) get no clarification beyond their names/enums.
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?
States a specific verb and resource ('List directories and listing sites where an indie product can be submitted') plus the data provenance (open launch-directories dataset, CC BY 4.0). The resource is narrow enough to separate it from siblings like list_categories or search_projects, and it names run_launch_check as a companion step.
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?
Gives concrete usage guidance: 'Use checked=true for source-backed options' and 'Run run_launch_check on the product site before submitting,' which places it in a workflow. It lacks any when-not-to-use guidance or explicit contrast with the other list/search siblings, so it stops 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.
run_launch_checkAInspect
Run the PostLaunchKit launch check on a public website. Returns how many checks passed (passed, total), each check with status pass or fail and a fix for failures, and a report link. 20 checks per IP per day. Public sites only.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public website to check, for example https://example.com |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses the return shape (passed/total counts, per-check status with a fix for failures, a report link) and a concrete rate limit of 20 checks per IP per day. It omits auth requirements and whether the check is idempotent or how long it takes, keeping it short of a 5.
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?
Three tight sentences, front-loaded with the action and target, then the return contents, then the hard limits. No filler and every clause carries 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?
With no output schema and no annotations, the description compensates by explaining what is returned and the rate cap. It is essentially complete for a single-parameter read-style tool, though an agent would still benefit from knowing about auth or timeout behavior.
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?
Only one parameter exists and the schema already documents it at 100% coverage, so the baseline is 3. The description adds real constraint value by restricting the URL to public sites, which the schema's 'Public website to check' phrasing only weakly conveys.
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?
States a specific verb and resource (run the PostLaunchKit launch check) on a clearly scoped target (a public website), which no sibling tool overlaps with. An agent can identify this as the site-auditing tool without opening the schema.
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 constrains usage with 'Public sites only' and gives a rate limit, which implies the appropriate context. However, it never states when to prefer this tool or what to do for non-public/authenticated targets, leaving usage guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_projectsCInspect
Search the PostLaunchKit directory of human-reviewed free tools and projects, including AI agent tooling. Returns published entries only.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | ||
| page | No | ||
| query | No | Text to search for in names, descriptions and tags. | |
| category | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden, and it does disclose one real behavior: unpublished entries are excluded from results. However, it says nothing about pagination behavior despite a 'page' parameter, result ordering/relevance, result count limits, or authentication requirements — all material for a 4-parameter search 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?
Two short sentences, with the core scope (what corpus is searched) front-loaded ahead of the result-scope caveat. Nothing is redundant. It is efficient, though it spends its brevity on scope rather than on operationally useful detail.
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 4-parameter, no-annotation, no-output-schema tool, the description omits filtering semantics, pagination, and result format. An agent knows what the tool searches but not how its filters compose or what a response looks like — significant gaps given zero structured behavioral metadata.
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 25%: only 'query' is documented in the schema, while 'tag', 'page', and 'category' (which has an enum) have no descriptions. The description adds no information about any of them — not whether tag and category can be combined, whether query matches tags, or how paging behaves — so the coverage gap is left fully unaddressed.
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?
States a specific verb (search) and a specific resource (the PostLaunchKit directory of human-reviewed free tools/projects), scoping it to published entries. It is clearly distinguishable from get_project, which implies retrieval of a single entry. It stops short of naming siblings like list_categories or explaining how that differs from this search.
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 statement of when to use this tool versus get_project, list_categories, or list_launch_directories, and no prerequisite or exclusion guidance. The only hint — 'Returns published entries only' — describes result scope, not invocation conditions. The agent must infer usage entirely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_projectAInspect
Suggest a product for the directory. The submission is saved as pending and reviewed by a person; nothing is published automatically.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Official website or app-store URL. | |
| name | Yes | ||
| tags | No | ||
| contact | No | Optional private email. | |
| why_try | Yes | What a user can do with the free option. | |
| category | Yes | ||
| logo_url | No | Optional public URL of a square logo (PNG, JPG, WebP or GIF, up to 2 MB). Resized to 256x256; fetch failures never reject the submission. | |
| one_liner | Yes | ||
| agent_name | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description carries the full burden and does disclose the key post-condition: the submission is stored as pending, human-reviewed, and never auto-published. That is meaningful lifecycle context an agent cannot get elsewhere. It stops short of covering failure handling, duplicate rejection, or what identifier is returned.
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, front-loaded with the action and immediately followed by the review/pending constraint. Nothing is redundant or padded.
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 9-parameter mutation tool with no output schema and no annotations, the description covers only the review lifecycle. It omits what the caller gets back (submission ID/status), field expectations for the five required parameters, and duplicate-handling behavior, leaving real gaps.
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 44%, so the description needs to compensate, but it says nothing about any of the 9 parameters. Undocumented fields such as name, one_liner, tags, category, and agent_name rely entirely on bare schema types; the description adds zero meaning beyond structure.
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?
States a specific verb and resource: 'Suggest a product for the directory.' That is clearly a write/submission action, which separates it from the read-oriented siblings (get_project, search_projects, list_categories). It does not explicitly name a sibling to disambiguate against, keeping it below a 5.
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 use case (proposing a new product) but gives no explicit guidance on when to prefer this over siblings, no prerequisite such as checking for duplicates with search_projects first, and no exclusions. Usage is inferred rather than stated.
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.
2 tool updates
- Changed
search_projects1 field changed- changed
Input schema / properties / category / enumPrevious value: -[ - "utilities", - "productivity", - "developer", - "education", - "sports", - "environment", - "ai-agents" -]New value: +[ + "ai-agents", + "developer", + "design-media", + "productivity", + "business", + "finance", + "games", + "education", + "health", + "utilities" +]
- Changed
submit_project1 field changed- changed
Input schema / properties / category / enumPrevious value: -[ - "utilities", - "productivity", - "developer", - "education", - "sports", - "environment", - "ai-agents" -]New value: +[ + "ai-agents", + "developer", + "design-media", + "productivity", + "business", + "finance", + "games", + "education", + "health", + "utilities" +]
1 tool update
- Changed
submit_project1 field changed- added
Input schema / properties / logo_urlAdded value: +{ + "description": "Optional public URL of a square logo (PNG, JPG, WebP or GIF, up to 2 MB). Resized to 256x256; fetch failures never reject the submission.", + "type": "string" +}
1 tool update
- Changed
list_launch_directories5 fields changed- added
Input schema / properties / badge_requirementAdded value: +{ + "enum": [ + "required", + "optional", + "none" + ], + "type": "string" +} - added
Input schema / properties / checkedAdded value: +{ + "description": "Only source-backed eligibility and free-tier options; not guaranteed approval.", + "type": "boolean" +} - added
Input schema / properties / link_evidenceAdded value: +{ + "enum": [ + "provider_claim", + "observed_listing", + "unknown" + ], + "type": "string" +} - added
Input schema / properties / link_typeAdded value: +{ + "enum": [ + "dofollow", + "nofollow", + "dofollow_with_badge" + ], + "type": "string" +} - added
Input schema / properties / product_typeAdded value: +{ + "description": "Public product class, such as software, digital_product or website.", + "type": "string" +}
6 tool updates
- First observed
get_project - First observed
list_categories - First observed
list_launch_directories - First observed
run_launch_check - First observed
search_projects - First observed
submit_project
Related MCP Connectors
Search a launch directory of new products, and submit and publish your own listing.
Toolfound is the launch platform and tool directory built for makers and their agents. Through this hosted MCP server, agents can search Toolfound's directory, find alternatives, see what's trending and launching, read full listing details and the launch calendar, and prep and submit a free launch, all without an account.
Scan MCP tool definitions for poisoning, look up server history, count tool-list tokens. Free.
Launchfiles hosted MCP: free page radars (design UX, search repair, deploy trust) + workspace tools.
Related MCP Servers
AlicenseAqualityCmaintenanceEnables AI agents to search launched software products, inspect weekly leaderboards and Hall of Fame winners, check upcoming launch calendar availability, and retrieve full product details. It can also draft a new product listing from a supplied URL, returning a private review link without publishing or charging.61MIT
SubmitMap MCP serverofficial
AlicenseNot gradedqualityCmaintenanceEnables searching a hand-curated directory of product launch platforms and startup directories, checking which ones a project qualifies for, and planning, executing, and tracking submissions through an agent's browser with optional authenticated account access.265MIT- AlicenseNot gradedqualityAmaintenanceEnables users to search and compare open-source AI agent tools by live GitHub activity, view tool details and alternatives, submit tools, check submission status, and find launch directories through an AI assistant.MIT
- AlicenseAqualityDmaintenanceSearch, inspect and compare infrastructure tools for AI agents from a checked directory.4MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.