@true402.dev/mcp-server

chat

Send chat completion requests to LLMs through a pay-per-call x402 service on Base, requiring a funded wallet.

Instructions

Send a chat completion request to an LLM via true402 (PAID x402 service, USDC on Base). Requires a funded wallet (WALLET_PRIVATE_KEY) on the MCP server.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model": "<model>",
      "messages": "<messages>"
    },
    "name": "chat"
  }
}

Input Schema

Name	Required	Description
`model`	Yes	Model ID (e.g. gpt-4o, claude-3-5-sonnet)
`messages`	Yes	Chat messages
`max_tokens`	No	Maximum tokens to generate

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.7.1Jun 20, 2026

TDQS

A3.7/5.0

Behavior3/5

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

No annotations provided, so the description carries the burden. It discloses payment requirement and wallet setup, but does not mention rate limits, error handling, or consequences of insufficient funds. The description partially covers behavior but leaves gaps.

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?

Two sentences, front-loaded with the primary action, and no wasted words. Every sentence adds necessary information about the service and prerequisite.

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 tool has 3 parameters (2 required), no output schema, and no annotations, the description is minimal. It covers the payment aspect but lacks details on model availability, response format, or error scenarios, making it incomplete for a transactional tool.

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 coverage is 100% with detailed descriptions for each parameter (model, messages, max_tokens). The description adds no extra semantics beyond what the schema already provides, earning the baseline score.

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 sends a chat completion request to an LLM via a specific paid service (true402). The verb 'send' and resource 'chat completion request' are explicit, and the service detail distinguishes it from sibling tools.

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 mentions the paid nature and wallet requirement, providing context on when to use it (if funded). However, it lacks explicit guidance on when not to use it or alternatives, leaving the AI to infer from sibling tool names.

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