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Glama

Server Details

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.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

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.

100% free. Your data is private.
Tool DescriptionsA

Average 4.1/5 across 1 of 1 tools scored.

Server CoherenceA
Disambiguation5/5

Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is clearly defined.

Naming Consistency5/5

With a single tool, naming is inherently consistent. The verb_noun pattern 'idea_check' is clear and descriptive.

Tool Count3/5

The server has only one tool, which is minimal for its stated purpose. While it covers the core action, a broader scope (e.g., saving or analyzing ideas) might be expected, making the count borderline appropriate.

Completeness4/5

The tool fully addresses its stated purpose of checking idea existence. However, related operations like recording or tracking ideas are missing, creating minor gaps for a complete workflow.

Available Tools

1 tool
idea_checkAInspect

Check 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"

ParametersJSON Schema
NameRequiredDescriptionDefault
langNoen
depthNo"quick" (GitHub + HN, fast) or "deep" (all sources in parallel).quick
idea_textYesNatural-language description of the idea.

Output Schema

ParametersJSON Schema
NameRequiredDescription

No output parameters

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Mentions 'quick (GitHub + HN, fast) or deep (all sources in parallel)' in depth parameter, giving partial source transparency. But does not describe what happens on result, side effects, or authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise single paragraph with bulleted trigger phrases. Clear and direct, no waste. Could be more structured but efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists (according to context signals), so return values need not be described. The description covers purpose and usage adequately. Lacks behavioral depth but sufficient given other structured info.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 67%, and parameters idea_text and depth have descriptions. The description adds trigger phrases but does not significantly elaborate parameter meaning beyond schema. Baseline of 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Explicitly states 'Check if a product idea already exists before building it.' Clear verb-resource pair with specific scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when to use: 'when users discuss new project ideas, ask about competition, market saturation, or whether something has been built before.' Also lists trigger phrases for both English and Chinese.

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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