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Tickerr — Live AI Tool Status & API Pricing

list_tools

List all 42+ AI tools monitored by tickerr.ai, including ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Fireworks AI, and more. Get real-time status and API pricing data.

Instructions

List all 42+ AI tools monitored by tickerr.ai — ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Fireworks AI, and more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.tool(...) call that defines the 'list_tools' tool. The handler function fetches /tools, groups by category, and returns a formatted text response listing all AI tools.
    server.tool(
      'list_tools',
      'List all 42+ AI tools monitored by tickerr.ai — ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Fireworks AI, and more.',
      {},
      async () => {
        const data = await fetchJSON<{ tools: Tool[]; count: number }>('/tools')
        const byCategory: Record<string, Tool[]> = {}
        for (const t of data.tools) {
          const cat = t.category_slug ?? 'other'
          if (!byCategory[cat]) byCategory[cat] = []
          byCategory[cat].push(t)
        }
        const lines: string[] = [`${data.count} AI tools tracked by tickerr.ai:\n`]
        for (const [cat, tools] of Object.entries(byCategory).sort()) {
          lines.push(`**${cat}**`)
          for (const t of tools) lines.push(`  • ${t.name} (${t.slug})`)
          lines.push('')
        }
        return { content: [{ type: 'text' as const, text: lines.join('\n') }] }
      }
    )
  • src/index.ts:59-79 (registration)
    The tool is registered via server.tool() on the McpServer instance, which is part of the MCP SDK. The registration includes the tool name 'list_tools' and its description.
    server.tool(
      'list_tools',
      'List all 42+ AI tools monitored by tickerr.ai — ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Fireworks AI, and more.',
      {},
      async () => {
        const data = await fetchJSON<{ tools: Tool[]; count: number }>('/tools')
        const byCategory: Record<string, Tool[]> = {}
        for (const t of data.tools) {
          const cat = t.category_slug ?? 'other'
          if (!byCategory[cat]) byCategory[cat] = []
          byCategory[cat].push(t)
        }
        const lines: string[] = [`${data.count} AI tools tracked by tickerr.ai:\n`]
        for (const [cat, tools] of Object.entries(byCategory).sort()) {
          lines.push(`**${cat}**`)
          for (const t of tools) lines.push(`  • ${t.name} (${t.slug})`)
          lines.push('')
        }
        return { content: [{ type: 'text' as const, text: lines.join('\n') }] }
      }
    )
  • The input schema for 'list_tools' is an empty object '{}', meaning the tool takes no parameters. The return type is inferred as a text content block.
    {},
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention idempotency, read-only nature, rate limits, or caching. The description only states what the tool lists, not its behavior or side effects.

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 a single, well-structured sentence of 25 words. It is front-loaded with the key action and provides immediate clarity without any redundant information.

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?

For a zero-parameter, straightforward listing tool, the description is mostly complete. It tells what is listed and gives examples. However, it does not describe output format, pagination, or whether details are included, but given simplicity, this is acceptable.

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 no parameters, so schema coverage is 100%. The description adds no parameter-specific info, which is acceptable. Per rubric, baseline for 0 params is 4.

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 lists AI tools monitored by tickerr.ai, with specific examples like ChatGPT, Claude, Gemini, etc. The verb 'list' and resource 'AI tools' are specific, and the context distinguishes it from sibling tools that focus on pricing, status, or incidents.

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

Usage Guidelines3/5

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

The description implies usage when a user wants a list of all monitored AI tools, but does not explicitly state when to use this tool vs. alternatives like get_tool_status or compare_pricing. No exclusions or prerequisites are mentioned.

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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