# fkiene/llmtrim

> Local proxy that compresses your LLM API requests so you pay less, with no change to the answers. Trims wasted tokens from prompts, history, tool output, and code before they're sent: -31% input / -74% output, measured live. Any provider, no extra model calls. Also an MCP server and embeddable library (Rust, Python, Ruby, Kotlin, Swift, JS/TS).

## Fast Facts & Telemetry
- **Canonical URL**: https://githubrepo.cloud/repo/fkiene/llmtrim
- **GitHub Source**: https://github.com/fkiene/llmtrim
- **Global Rank**: #13,029 on GitHubRepo
- **Stars**: 253
- **Forks**: 23
- **Open Issues**: 13
- **Primary Language**: Rust
- **Software License**: MPL-2.0
- **Last Commit / Push**: Oct 20, 2026
- **Topics**: agentic-coding, ai, anthropic, claude-code, cost-reduction, developer-tools, llm, llmops, mcp, mitm-proxy, openai, prompt, prompt-compression, prompt-engineering, proxy, rust, token-optimization

## Open Source Alternative to OpenAI API & ChatGPT
llmtrim is a privacy-first, self-hostable open source alternative to **OpenAI API & ChatGPT** (Pay-per-token pricing with zero private data guarantees).
- **Proprietary SaaS Pain Point**: Confidential business data and proprietary code sent over external third-party cloud APIs.
- **Explore All OpenAI API & ChatGPT Alternatives**: https://githubrepo.cloud/alternatives/openai

## Project Overview
llmtrim is an open-source project written in Rust: Local proxy that compresses your LLM API requests so you pay less, with no change to the answers. Trims wasted tokens from prompts, history, tool output, and code before they're sent: -31% input / -74% output, measured live. Any provider, no extra model calls. Also an MCP server and embeddable library (Rust, Python, Ruby, Kotlin, Swift, JS/TS).

Engineered for speed, consistency, and developer ease, it solves common hurdles in agentic-coding, ai, anthropic. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

## Key Features
- Optimized execution pipeline written in Rust for predictable speed.
- Zero-friction configuration with comprehensive sensible defaults out of the box.
- Cross-platform runtime support across Linux, macOS, and Windows environments.
- Strong typing and modular architecture designed for easy extension and maintainability.
- Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
- Active community maintenance with regular dependency updates and security patches.

## Installation & Quick Start
### Linux
```bash
cargo install llmtrim
```

### macOS
```bash
cargo install llmtrim # or: brew install llmtrim
```

### Windows
```bash
cargo install llmtrim
```

## System Requirements & Architecture
- **Supported Platforms**: macOS, Linux, Windows
- **Runtime Dependencies**: Rust toolchain (rustc / cargo >= 1.70)
- **Architecture**: x86_64, ARM64 (Apple Silicon & Graviton)

## How It Works
llmtrim coordinates its core functionality through a modular Rust pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

## Production Use Cases
### Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with llmtrim.

### Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.

### Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.

### Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.

## Target Audience
Developers and engineering teams building with Rust, seeking reliable, tested, and actively maintained tooling for production workloads.

## Strengths
- Active community backing with 253 GitHub stars and verified adoption.
- Permissive open-source distribution under the MPL-2.0 license.
- Built in Rust for high execution speed and developer familiarity.
- Cross-platform compatibility across modern Linux, macOS, and Windows environments.
- Clean modular design allowing flexible configuration and pipeline integration.

## Considerations
- Requires familiarity with Rust and modern CLI workflows.
- Ecosystem extensions may require manual configuration depending on environment constraints.
- Active development roadmap means breaking API changes may occur across major versions.

---
*Analyzed, indexed, and verified by GitHubRepo (https://githubrepo.cloud). Free public telemetry for open source creators and developers.*