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pythia-the-oracle

pythia-oracle-mcp

Official

get_integration_guide

Get Solidity code for integrating Pythia into a smart contract by selecting a tier and optional chain. Returns embedded addresses for the chosen chain and lists every chain where that tier's consumer is deployed.

Instructions

Get Solidity code to integrate Pythia into a smart contract.

Args: tier: 'discovery' (single value), 'analysis', 'speed', or 'complete'. chain: Optional chain key (e.g. 'mainnet', 'amoy', 'arbitrum'). When unset, the embedded Solidity uses the first available chain's addresses (Polygon mainnet by convention) and the prose lists every chain where this tier's consumer is deployed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNodiscovery
chainNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.1
    • addedInput schema / properties / chain
      Added value: +{
      +  "default": "",
      +  "title": "Chain",
      +  "type": "string"
      +}
  2. Addedv0.3.0
  3. Removedv0.2.4
  4. First observedv0.2.2

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It does well by explaining the default chain behavior, that the embedded Solidity uses the first available chain's addresses, and that the prose lists every deployed chain. It does not discuss error cases or authentication, but the key behavioral nuance is transparent.

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 concise, front-loaded with the core purpose, and then uses a brief Args section to clarify parameters. Every sentence contributes useful information without redundancy or filler.

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

Completeness5/5

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

Given two optional parameters and an output schema, the description fully covers the needed invocation context: what the tool returns, valid tier values, chain behavior, and defaults. Nothing critical is missing for an agent to select and call this tool correctly.

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?

Schema description coverage is 0%, so the description must compensate. It lists the valid tier values and explains the chain parameter's optionality and default behavior with concrete examples. This gives agents enough semantic meaning to invoke the tool correctly, though a complete chain enum list would be even stronger.

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 states a specific action and resource: 'Get Solidity code to integrate Pythia into a smart contract.' This clearly differentiates it from sibling guides like get_events_guide or get_visions_guide, which presumably cover different integration topics.

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 explains how to choose tier and chain values, and what happens when chain is unset. However, it does not explicitly state when to prefer this tool over sibling guides, nor does it mention any alternatives or exclusions. Usage context is implied rather than directly stated.

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