Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt — returns a 0-100 reality signal before you build. Supports quick (2 sources) and deep (5 sources) parallel search.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.2/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion between tools.
Single tool name follows a clear verb_noun pattern, consistent by default.
One tool feels too thin for a server; a broader set for idea validation would be more appropriate.
The tool covers the primary check but lacks additional functionality like saving or comparing ideas.
idea_checkAInspectCheck if a product idea already exists before building it.
Use when users discuss new project ideas, ask about competition, market saturation, or whether something has been built before.
Trigger phrases: "has anyone built", "does this exist", "check competition", "is this idea original", "有沒有人做過", "市場上有類似的嗎", "幫我查這個點子"
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | en | |
| depth | No | "quick" (GitHub + HN, fast) or "deep" (all sources in parallel). | quick |
| idea_text | Yes | Natural-language description of the idea. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the transparency burden. It implies a non-destructive 'check' but does not explicitly describe data sources, rate limits, or that it performs only reads. The depth parameter in the schema mentions 'GitHub + HN' and 'all sources', adding some transparency, but the main description does not elaborate on these behaviors.
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 concise and well-structured: a one-sentence purpose, a short usage paragraph, and a bullet-like list of trigger phrases. It is front-loaded and every line earns its place without redundant fluff.
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 tool's simplicity, no siblings, and the presence of an output schema, the description covers essential context: purpose, when to use, and trigger examples. It stops short of being a 5 because the main description does not directly state data sources or any limitations, though the schema partially fills that gap.
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 67% (idea_text and depth have descriptions; lang does not). The description itself adds no parameter-specific detail, but the schema covers the important parameters. The lang parameter is self-explanatory via its enum and default. Overall, the description adds marginal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check if a product idea already exists before building it.' It uses a specific verb ('check') and resource ('product idea'), making the function unambiguous. Although there are no siblings to distinguish from, the purpose is immediately evident.
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 explicit usage guidance: 'Use when users discuss new project ideas, ask about competition, market saturation, or whether something has been built before.' It also lists concrete trigger phrases in both English and Chinese, giving the agent clear signals for when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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.
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