LaunchOnIt MCP Server
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@LaunchOnIt MCP ServerWho's leading this week's launch leaderboard on LaunchOnIt?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
LaunchOnIt MCP Server š
Official Model Context Protocol (MCP) server for LaunchOnIt ā the launch platform for indie hackers and modern software makers.
Connect this server to Claude Desktop, Cursor, Windsurf, Cline, Antigravity, or any MCP-compatible agent to search products, inspect weekly rankings, check launch calendar availability, and draft new product launches.
⨠Features
š Real-Time Product Search: Search through hundreds of launched SaaS tools, indie applications, and dev utilities.
š Weekly Leaderboards & Winners: Fetch the current live week rankings or historical podium finishers from the Hall of Fame.
š Launch Calendar Availability: Inspect free launch slots and plans for upcoming cohorts.
š¤ AI Product Submissions: Draft a product launch by simply providing a URL. LaunchOnIt automatically crawls metadata, writes a launch draft, and returns a private review link for the maker to edit and publish.
ā” Zero Configuration: Public Streamable HTTP JSON-RPC endpoint. No API keys or account setup required to connect.
Related MCP server: skillsindex-mcp
š Quickstart & Configuration
Option A: Direct Streamable HTTP (Recommended)
Most modern MCP clients support direct HTTP / SSE remote connections without installing local Node packages.
Endpoint URL: https://launchon.it/api/mcp
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"launchonit": {
"url": "https://launchon.it/api/mcp"
}
}
}Cursor (.cursor/mcp.json)
{
"mcpServers": {
"launchonit": {
"url": "https://launchon.it/api/mcp"
}
}
}Windsurf (~/.codeium/windsurf/mcp_config.json)
{
"mcpServers": {
"launchonit": {
"serverUrl": "https://launchon.it/api/mcp"
}
}
}Option B: Local CLI / Stdio Bridge
For clients that require a local command (stdio transport):
npx -y launchonit-mcpClaude Desktop (Local Stdio)
{
"mcpServers": {
"launchonit": {
"command": "npx",
"args": ["-y", "launchonit-mcp"]
}
}
}Claude Code CLI
claude mcp add launchonit -- npx -y launchonit-mcpš ļø Available Tools
Tool | Type | Description | Arguments |
| Read | Keyword search across every product launched on LaunchOnIt, ranked by community upvotes. |
|
| Read | Fetch ranked products for an ISO week (e.g. |
|
| Read | Retrieve complete product details: tagline, story, problem solved, pricing, tech stack, and links. |
|
| Read | Top 3 podium winners from past launch weeks (Hall of Fame). |
|
| Read | Free launch slots remaining in the live week and subsequent weeks, plus launch tiers. |
|
| Write (Draft) | Scrapes a website URL, generates a full listing draft, and returns a private review link. |
|
š Safety & Privacy
Non-destructive Drafting: The
submit_producttool only creates a private draft. It never publishes a product publicly and never initiates payment. The agent receives a secure URL where the product owner signs in, verifies their details, and chooses when to launch.Rate Limits: The public endpoint is protected by intelligent rate limiting (60 requests/minute for queries, 5 drafts/hour per IP).
Open & Free: All discovery and research tools are 100% free and open to the community.
š” Example AI Prompts
Once connected, you can ask your AI:
"Search LaunchOnIt for AI developer tools that launched recently."
"Who is currently leading this week's launch leaderboard on LaunchOnIt?"
"Show me the top 3 podium winners from the last 4 weeks on LaunchOnIt."
"I just built https://mycooltool.com. Can you draft a submission for me on LaunchOnIt?"
š Useful Links
Platform: https://launchon.it
MCP Documentation: https://launchon.it/mcp
Hall of Fame: https://launchon.it/winners
Well-Known MCP Discovery Card: https://launchon.it/.well-known/mcp.json
š License
MIT Ā· LaunchOnIt
Available Tools
6 toolsget_launch_calendarLaunch calendarARead-onlyIdempotent
Free launch slots left in the live week and the weeks after it, plus the launch plans and prices. Use it to tell a maker when they would launch.
| Name | Required | Description | Default |
|---|---|---|---|
| weeks | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds meaningful context about the data returnedāfree slots, plans, and pricesābut does not disclose details like ordering, availability semantics, or response shape.
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 tight sentences front-load the core data content and end with a clear usage directive. There is no filler, repetition of the title, or extraneous 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 simple read-only tool with one optional parameter, the description is mostly sufficient: it names the output contents and the intended use. However, the complete absence of parameter documentationāespecially with no output schemaāleaves a noticeable gap for an agent deciding how to set 'weeks'.
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 has 0% description coverage for its only parameter, 'weeks', and the description never mentions how this parameter controls the returned calendar. The phrase 'the live week and the weeks after it' hints at the domain but does not explain the parameter's effect, default, or range.
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 names a specific resourceāfree launch slots, launch plans, and pricesāand states a concrete use: tell a maker when they would launch. This clearly distinguishes the tool from siblings like get_weekly_leaderboard or submit_product without needing their schemas.
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 explicitly says when to use the tool: to tell a maker when they would launch. It gives clear context but does not list exclusions or compare against competing sibling tools, so it falls just 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.
get_productGet productARead-onlyIdempotent
Full public listing for one product: tagline, description, who it's for, the problem it solves, pricing, tech stack, links and upvotes.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The slug from launchon.it/products/{slug}. |
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 covered. The description adds 'public' context and enumerates the listing fields, which is useful, but it does not disclose additional behaviors such as authentication requirements, rate limits, or error conditions. It neither contradicts the annotations nor adds substantial behavioral depth 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 a single, well-structured sentence that leads with the core purpose and then lists the content included. Every phrase earns its place, and there is no redundant or filler text.
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 tool with one well-documented parameter, safety annotations, and no output schema, the description provides enough context by enumerating the returned listing fields. An agent can understand what it will receive and how to invoke the tool correctly without missing critical information.
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% and the sole parameter 'slug' is already documented as 'The slug from launchon.it/products/{slug}.' The description does not add parameter-level meaning, but the schema fully carries that burden, so the 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 states a specific verb and resource ā 'get' a single product ā and enumerates exactly what the listing contains: tagline, description, target audience, problem solved, pricing, tech stack, links, and upvotes. This clearly distinguishes it from sibling tools like search_products or get_launch_calendar by focusing on one product's full public 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?
The description implies this tool is used when you need the full public listing for one product, rather than searching or viewing calendars/leaderboards. However, it does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or conditions such as 'use search_products when you don't have a slug.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_weekly_leaderboardWeekly leaderboardARead-onlyIdempotent
Ranked products for one ISO week, by community upvotes. Defaults to the live week, which closes Sunday 23:59 UTC.
| Name | Required | Description | Default |
|---|---|---|---|
| week | No | ISO week like 2026-W39. Omit for the live week. | |
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, covering safety. The description adds useful context: the ranking basis (upvotes) and the week's closing time, which informs expected data freshness. This goes beyond the annotations without contradiction.
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 with no redundancy. The core purpose is front-loaded, and the default behavior is stated efficiently. 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?
The tool is simple (two optional parameters, no output schema). The description covers the purpose, ranking basis, and default week behavior. It does not specify the return format, but given no output schema and the simplicity, it is reasonably complete. Minor gap: no mention of limit's effect on results, but that's inferable.
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 50% (week has a description, limit does not). The description adds context for the week parameter by explaining the default live week, but does not elaborate on the limit parameter or its meaning beyond the schema. Since coverage is moderate, the description could compensate more, but it partially does.
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 (get ranked products), the resource (products for one ISO week), and the ranking basis (community upvotes). It clearly distinguishes from siblings like get_product (single product) and get_winners (likely a different selection), so an agent can tell them apart.
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 clarifies the default behavior (live week, closing Sunday 23:59 UTC) but does not explicitly mention when to use this tool over alternatives or any exclusions. The context implies weekly leaderboard use, but no explicit when-not guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_winnersWeekly winnersARead-onlyIdempotent
Top 3 podium finishers from recent weeks, newest week first. These are the Hall of Fame entries on /winners.
| Name | Required | Description | Default |
|---|---|---|---|
| weeks | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful ordering and scope context ('newest week first', 'Hall of Fame entries'), which goes beyond annotations. It does not mention response format or edge cases, but those are less critical given the safety hints.
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 tight sentences with no filler. The key factsāresource, ordering, and domain locationāare front-loaded and every sentence 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 simple read-only tool with one optional parameter and safety hints from annotations, the description covers the essential facts: what is returned, ordering, and domain context. It does not spell out the exact meaning of 'weeks', but the schema and context make it reasonably clear.
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 single parameter 'weeks' is not directly explained in the description, though the phrase 'from recent weeks' hints at it. The schema supplies defaults, min, and max, so an agent can infer basic semantics, but the description itself adds little direct parameter guidance.
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 states a specific resource ('Top 3 podium finishers') and clear scope ('from recent weeks, newest week first'). It also grounds the resource ('Hall of Fame entries on /winners'), which helps distinguish it from sibling tools like get_weekly_leaderboard.
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 such as get_weekly_leaderboard or get_launch_calendar. The description implies a retrieval use case but never states when this tool is preferred or when to avoid it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_productsSearch productsARead-onlyIdempotent
Keyword search across every product that has launched on LaunchOnIt. Matches name, tagline and description, most upvoted first.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | Keywords, e.g. "email marketing" or "open source analytics". |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavior by specifying that it matches name, tagline, and description and sorts by upvotes, but it omits pagination or result-format details. This is adequate 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 two short sentences with no filler. The first sentence states the core action and scope; the second adds matched fields and ordering. Every part 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 keyword search tool with two parameters and annotations covering read-only/idiompotent behavior, the description covers scope, matched fields, and sort order. It omits details about the return shape, but since there is no output schema and complexity is low, this is a minor gap rather than a critical one.
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 already describes query with examples, and the description adds that the query matches name/tagline/description, clarifying search semantics. The limit parameter lacks a schema description and is not mentioned in the description, though its constraints (default 10, max 25) are present in the schema. With 50% schema coverage, the description partially compensates but not fully.
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 opens with 'Keyword search across every product that has launched on LaunchOnIt', naming a specific verb, resource, and scope. It distinguishes this from siblings like get_product (single-product retrieval) and get_weekly_leaderboard by focusing on keyword search, and further details matched fields and ordering.
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 conveys that this tool is for keyword search, so usage context is implied. However, it does not explicitly mention alternative tools or state when not to use it, leaving the agent to infer that get_product might be better for known IDs or that leaderboard tools serve different needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
submit_productSubmit productA
Starts a launch for a product URL. LaunchOnIt reads the site, drafts the listing (name, tagline, description, story, pricing, categories) and returns a private review link. The maker opens the link, signs in, edits and publishes. Nothing goes live and nothing is charged from this call.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The product's website, e.g. https://example.com | |
| title | No | Product name. Drafted from the site if omitted. | |
| tagline | No | One line, 10-50 characters. Drafted from the site if omitted. | |
| description | No | Drafted from the site if omitted. | |
| pricing_type | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=false, destructiveHint=false and openWorldHint=true; the description adds meaningful non-annotation context by stating nothing goes live and nothing is charged, plus that a private review link is returned and a human must sign in to publish. It does not address idempotency (repeat calls), which the annotations flag as non-idempotent.
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 ordered as action, result, and safety guarantee. No filler, and the most decision-relevant facts (what it starts, what it returns, no charge) lead.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description carries the return-value burden and does so by naming the private review link and the human publish step. The shape of the response beyond the link is left implicit, but an agent has enough to call and interpret it.
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 80% and all five parameters are already documented, including the 'drafted if omitted' behavior. The description's list of drafted fields mirrors the schema rather than adding syntax or format detail, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('starts a launch for a product URL') and enumerates what the tool produces (drafted listing, private review link). Every sibling tool is a read/get/list operation, so this write-oriented tool is unmistakably distinct.
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?
Clearly frames the context of use: submit a URL to kick off drafting, then a human reviews and publishes. It does not explicitly name when NOT to use it or point at a sibling alternative, but with the remaining tools being read-only, the selection is unambiguous.
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.
6 tool updates
v1.0.0- First observed
get_launch_calendar - First observed
get_product - First observed
get_weekly_leaderboard - First observed
get_winners - First observed
search_products - First observed
submit_product
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose: search_products is broad keyword search, get_product retrieves one full listing, get_weekly_leaderboard ranks a single week's products, get_winners shows top 3 from recent weeks, get_launch_calendar covers availability and pricing, and submit_product is the only write action. Overlap is minimal and descriptions make boundaries clear.
All six tools follow a consistent snake_case verb_noun pattern: search_products, get_weekly_leaderboard, get_product, get_winners, get_launch_calendar, submit_product. There are no mixed conventions or vague names.
Six tools is well-scoped for a platform focused on product discovery, rankings, launch calendar, and submission. Each tool earns its place without redundancy or extreme thinness.
The surface covers core read operations and launch initiation, but there are minor gaps: no update/delete/cancel for launches, no way to browse by category, and the submission workflow hands off to a web link. These are workable but not a fully closed lifecycle within the MCP.
Maintenance
Related MCP Connectors
LaunchOnIt is a weekly launch platform and discovery directory for modern SaaS, developer tools, and AI startups. This MCP server connects AI assistants directly to LaunchOnItās live software catalog, rankings, and launch infrastructure. Search launched products, weekly leaderboards and podium winners, check open launch slots, and submit a product launch for review.
Launch board run by AI agents: find tools by what they do, launch products, vote, comment, discuss.
Search community-ranked software products: trending launches, details, and alternatives to a tool.
Launch once, get found everywhere: a product page built for search and AI, run from your AI agent.
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