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Documentation Index

Fetch the complete documentation index at: https://docs.ctxprotocol.com/llms.txt

Use this file to discover all available pages before exploring further.

Context Protocol Hero

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TypeScript SDK

Build with Node.js

Python SDK

Build with Python
LLMs are smart, but they lack the live facts your question actually needs. Context is a gateway to premium data feeds (the market intelligence normally locked behind steep monthly or annual subscriptions), unbundled into pay-per-response. Your agent buys exactly the facts a question needs at query time and drops them into its context window, so you get grounded, precise answers instead of confident guesses, without paying for a subscription you’d barely use.
The insight you pay $500/year for? Your agent could buy it for $0.10/response.

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Why use Context?

  • Grounded Answers, Not Guesses: Every response is assembled from live data the agent actually retrieved, or it tells you the marketplace can’t answer, instead of inventing numbers.
  • One Interface, Everything: Stop integrating APIs one by one. Use a single SDK to access any tool in the marketplace.
  • Zero-Ops: We’re the gateway to premium data tools that are usually locked behind steep monthly or annual subscriptions. We host the connections; you just send the JSON and get the result.
  • Agentic Discovery: Your Agent can search the marketplace at runtime to find tools it didn’t know it needed.
  • Simple Pricing: Pay per response for curated intelligence, or pay per call for raw data. Your choice.

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The Ecosystem

Context is not just a chatbot. It’s an economic engine for the AI era. We connect three distinct groups in a decentralized marketplace for Model Context Protocol (MCP) tools. Build a standard MCP server, paste your endpoint URL, set a price, and get paid in USDC when agents use your tool.

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For Users: The Context Agent

Ask anything and get a grounded answer built from live data: the agent buys the facts it needs on demand instead of guessing from stale training data. Real-time, read/write access to the world, one wallet, pay-per-response.

Auto Mode

Ask “Find the best yield on Base” and the Agent autonomously searches the marketplace, buys the necessary data tools, analyzes the returns, and presents the answer.

One Wallet

Pay for everything (from gas data to premium stock analysis) using a single USDC balance. No subscriptions, just pay-per-response.
Want proof? See Grounded vs. Synthetic: the same hard market question sent to a top frontier model and to Context, where the free model invents the market regime and Context returns grounded numbers, a rendered chart, and a verifiable verdict.

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For Tool Builders: The “App Store” for MCP

Monetize your data without building a frontend. Turn the insights people pay $500/year for into $0.10/response revenue you keep.
BenefitDescription
Build Once, Sell EverywhereCreate a standard MCP Server
Zero UI RequiredYou provide the API; our Agent provides the interface
Instant RevenueSet a price (e.g., $0.01/response). Get paid in USDC on Base every time an Agent successfully uses your tool

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For App Developers: The Universal Adapter

Build your own agents using the Context Protocol as your infrastructure layer. Every API you integrate means reading docs, managing auth keys, handling rate limits, parsing a unique response schema, and maintaining it when they change. Multiply that by 5 data sources and you’ve lost a week before writing any business logic.
1

One SDK, Hundreds of APIs

Instead of integrating CoinGecko, Tavily, and Weather APIs separately, just install @ctxprotocol/sdk (TypeScript) or ctxprotocol (Python). One auth token, one interface, consistent typed schemas.
2

Dynamic Discovery

Your agent can search the marketplace at runtime: client.discovery.search("gas prices"). It finds tools it didn’t know existed and uses them without human intervention.
3

Schema Inspection

Every tool exposes full Input/Output schemas. Your LLM can self-construct arguments and execute tools it has never seen before, with no hardcoded integrations.
4

Session Budgets, Not Blank Checks

Give your agent a spending limit (maxSpendUsd: "2.00") and let it explore. You control exactly how much it can spend per session.

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The npm/pip for AI Capabilities

“Context Protocol is npm/pip for AI capabilities.”Just as npm install or pip install gives you code other people wrote, Context gives your Agent capabilities other people built.
import { ContextClient } from "@ctxprotocol/sdk";

const client = new ContextClient({ apiKey: "sk_live_..." });

const answer = await client.query.run("What are the top whale movements on Base?");
console.log(answer.response);
Want more control? The SDK also supports Execute mode for per-call pricing with spending limits, which fits custom agent pipelines. See the Agentic Pattern guide or the SDK Reference.

Users

Start querying with Context

Builders

Monetize your MCP server

Developers

Integrate the SDK into your agents