Skip to main content
Glama
nadine302324-commits

Lexicon Intelligence

lexicon_compare_vs

Compare two vendors or products head-to-head using live evidence from 20 independent sources and PESTLE Triangulation to generate a structured comparison report.

Instructions

Head-to-Head VS comparison between two vendors or products. Retrieves live evidence from 20 independent web sources and applies PESTLE Triangulation to produce a structured comparison report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vendorAYesFirst vendor or product name
vendorBYesSecond vendor or product name
industryNoIndustry context (e.g. fintech, healthcare, SaaS)

Implementation Reference

  • index.js:10-22 (registration)
    The tool 'lexicon_compare_vs' is registered in the TOOLS array with its name, description, and inputSchema (schema definition).
    {
      name: "lexicon_compare_vs",
      description: "Head-to-Head VS comparison between two vendors or products. Retrieves live evidence from 20 independent web sources and applies PESTLE Triangulation to produce a structured comparison report.",
      inputSchema: {
        type: "object",
        properties: {
          vendorA:  { type: "string", description: "First vendor or product name" },
          vendorB:  { type: "string", description: "Second vendor or product name" },
          industry: { type: "string", description: "Industry context (e.g. fintech, healthcare, SaaS)" },
        },
        required: ["vendorA", "vendorB"],
      },
    },
  • The input schema for lexicon_compare_vs defines two required string parameters (vendorA, vendorB) and one optional string parameter (industry).
      inputSchema: {
        type: "object",
        properties: {
          vendorA:  { type: "string", description: "First vendor or product name" },
          vendorB:  { type: "string", description: "Second vendor or product name" },
          industry: { type: "string", description: "Industry context (e.g. fintech, healthcare, SaaS)" },
        },
        required: ["vendorA", "vendorB"],
      },
    },
  • index.js:86-86 (registration)
    The TOOL_MAP maps the tool name 'lexicon_compare_vs' to the remote endpoint 'lexicon.compare.vs' which is called via the MCP proxy.
    lexicon_compare_vs:          "lexicon.compare.vs",
  • The generic CallToolRequestSchema handler proxies all tool calls (including lexicon_compare_vs) by mapping the name via TOOL_MAP and forwarding to the remote MCP endpoint at BASE_URL/mcp/v1.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      const { name, arguments: args } = request.params;
      const remoteTool = TOOL_MAP[name];
      if (!remoteTool) {
        return { content: [{ type: "text", text: `Unknown tool: ${name}` }], isError: true };
      }
    
      const headers = { "Content-Type": "application/json" };
      if (API_KEY) headers["X-API-Key"] = API_KEY;
    
      const response = await fetch(`${BASE_URL}/mcp/v1`, {
        method: "POST",
        headers,
        body: JSON.stringify({
          jsonrpc: "2.0",
          id: 1,
          method: "tools/call",
          params: { name: remoteTool, arguments: args },
        }),
      });
    
      const data = await response.json();
      if (data.result) return data.result;
      return {
        content: [{ type: "text", text: JSON.stringify(data.error || data) }],
        isError: true,
      };
Behavior3/5

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

The description reveals that the tool retrieves live evidence from 20 sources and applies PESTLE Triangulation, providing some transparency. However, without annotations, it lacks details on potential side effects, required permissions, or output format.

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 extremely concise, consisting of two sentences that effectively front-load the purpose and key behavioral aspects. No superfluous words.

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

Completeness3/5

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

Given the absence of an output schema and the presence of sibling tools, the description is somewhat sparse. It explains the basic behavior but could better prepare the agent for interpreting results or handling errors.

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?

Input schema has 100% description coverage, so the baseline is 3. The description reinforces the schema by referring to 'vendors or products' and 'industry context', but adds no extra semantic nuance beyond what is already in the parameter descriptions.

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 core function: comparing two vendors or products head-to-head. It mentions retrieving live evidence and applying PESTLE Triangulation, making the purpose distinct from sibling tools like lexicon_compare_methodology or lexicon_compare_topic.

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 text implies when to use the tool (for comparing two vendors/products) but does not explicitly state when not to use it or suggest alternatives. No guidance on prerequisites or context limits is provided.

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/nadine302324-commits/lexicon-mcp-server'

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