Skip to main content
Glama
therealjlc1

SharpEdge MCP Server

by therealjlc1

get_pricing

Retrieve pricing plans and feature comparisons for SharpEdge AI's sports betting analysis service, including free tier and paid options.

Instructions

Get SharpEdge AI pricing information including free tier (1 edge per day), weekly plan ($19/week), and monthly plan ($49/month with 35% savings). Includes feature comparison across tiers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what information is returned (pricing tiers with specific details), but doesn't mention whether this requires authentication, rate limits, or other behavioral traits. The description adds value by specifying the content but doesn't fully compensate for the lack of annotations.

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

Conciseness5/5

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

The description is efficiently structured in two sentences with zero waste. The first sentence states the purpose and lists pricing tiers with specific details, while the second sentence adds important context about feature comparison. Every sentence earns its place.

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?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description provides complete context about what information is returned. It could be slightly more complete by mentioning the response format or whether authentication is required, but for a simple pricing lookup tool, it's largely adequate.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on the semantic content of the response, which is appropriate for a parameterless tool.

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?

The description clearly states the tool's purpose with specific verbs ('Get') and resources ('SharpEdge AI pricing information'), including detailed content about free tier, weekly plan, and monthly plan. It distinguishes itself from sibling tools like 'get_features' or 'get_sample_edges' by focusing specifically on pricing information.

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

Usage Guidelines4/5

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

The description implicitly suggests usage when pricing information is needed, but does not explicitly state when to use this tool versus alternatives like 'get_features' or provide exclusions. It offers clear context about what information is included, but lacks explicit guidance on when-not scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/therealjlc1/sharpedge-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server