Context7 and AI Docs Access

Access Revenium documentation from AI coding assistants via Context7 or llms.txt.

Use this page when you want an AI assistant or coding agent to retrieve Revenium documentation, schemas, and API guidance while it works. If you want an agent to query or operate Revenium itself, use MCP Server.

Context7 (Recommended)

Context7 provides automatic documentation retrieval via MCP. Your AI agent pulls relevant Revenium docs on demand — works with any MCP-compatible tool (Claude Code, Cursor, Windsurf, Continue, Cline, GitHub Copilot).

Add the Context7 MCP server to your agent's configuration:

{
  "mcpServers": {
    "context7": {
      "command": "npx",
      "args": ["-y", "@upstash/context7-mcp@latest"]
    }
  }
}

Refer to your tool's MCP documentation for the configuration file location.

Revenium Libraries on Context7

Documentation:

Library	Content
API Reference	Complete REST API reference with request/response schemas
Knowledge Base	Guides, quickstarts, and platform concepts

SDKs and Tools:

Library	Content
Python SDK	Unified Python middleware for OpenAI, Anthropic, Google, LiteLLM
Node Middleware	Unified TypeScript middleware for all supported providers
MCP Server	Zero-code AI metering via Model Context Protocol
Claude Code SDK	Claude Code telemetry export and usage tracking
CLI	Command-line interface for the Revenium platform

When querying Context7, use revenium as the search term to find these libraries.

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llms.txt

For browser-based AI tools (ChatGPT, Claude.ai, Gemini) or when MCP is unavailable, paste this URL into your conversation:

https://revenium.readme.io/llms.txt

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OpenAPI Specs

Full OpenAPI (OAS) documents are available for download at:

Revenium OpenAPI Spec Downloads

These are large files intended for code generation tools and schema validation, not for pasting into AI chat. For AI agent access to Revenium APIs, use Context7 or llms.txt instead.

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Related

• Integration Options — choose the right setup path

• MCP Server — connect MCP-compatible agents to Revenium

• OTLP Integration — OTLP endpoints and GenAI attribute mapping

Metering API Reference

Modality	API Reference
Completions	Meter AI Completion
Images	Meter AI Images
Video	Meter AI Video
Audio	Meter AI Audio