# supermemory Infinite Chat API

> Context engineering API extending LLM context across providers via proxy routing

Infinite Chat API by supermemory is a context engineering proxy that handles long conversation histories, state tracking, and memory management for any large language model. By prepending the supermemory endpoint to standard provider SDK calls, it backfills context, prunes redundant turns, and manages multimodal history without blowing up token usage. It prevents context pollution and degradation across multi-turn agent runs and coding co-pilots.

Website: https://supermemory.ai/blog/faster-smarter-reliable-infinite-chat-supermemory-is-context-engineering

## What it is for

- Maintain persistent context across multi-step coding agents without repeating prior chat turns
- Reduce token usage and latency in long-running chatbot conversations
- Persist multimodal context like past screenshots, audio, and structured data across sessions
- Track agent tool calls and results so agents avoid repeating actions

## Features

- Drop-in proxy integration by changing baseURL in existing OpenAI, Anthropic, or Gemini SDKs
- Multi-step agent support with automated conversation backfilling using conversation-id
- Context pruning and summarization to reduce context pollution and token costs
- Multimodal memory persistence across interaction turns
- Tool call tracking and awareness to avoid redundant function executions
- Long-context RAG that selectively surfaces relevant chunks

## Pricing

Freemium. Free tier available; usage-based API pricing via developer console.

## Details

- Type: Web app
- Category: [AI](https://xiry.app/topics/ai.md)
- Open source: no
- Platforms: API
- For: Developers building stateful AI agents, chatbots, and long-running co-pilots
- Alternative to: Mem0, LangChain Memory, Zep
- Tags: context engineering, llm, ai agents, memory, api proxy, rag

## Why it was saved

- [@DhravyaShah, 15 May 2025](https://x.com/DhravyaShah/status/1923123825111097387): Solves the context-length limit for building chat/agent products; directly relevant to building coding agents per the video's closing frame.

## Related

- [memary](https://xiry.app/resources/memary): Open-source persistent memory layer for autonomous AI agents using knowledge graphs (GitHub repo, Open source)
- [Primary Sources on Context Engineering](https://xiry.app/resources/primary-sources-on-context-engineering): Curated reading list of core engineering essays on agent context management. (List, Free)
- [ai-engineering-hub](https://xiry.app/resources/ai-engineering-hub): Open-source tutorials and project templates for LLMs, RAG, and AI agents. (GitHub repo, Open source)
- [8 Ways to Improve RAG Applications](https://xiry.app/resources/8-ways-to-improve-rag-applications): Practical architectural strategies to fix common failure modes in RAG systems (Tip, Free)
- [ACU - Awesome Agents for Computer Use](https://xiry.app/resources/acu-awesome-agents-for-computer-use): Curated collection of papers, tools, and frameworks for computer-controlling AI agents (Website, Free)
- [Agent Harness is the Real Product](https://xiry.app/resources/agent-harness-is-the-real-product): Architectural breakdown of AI agent harnesses, scaffolds, and context management patterns. (Framework, Free)

Updated 10 October 2026. Page: https://xiry.app/resources/supermemory-infinite-chat-api

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