Search Results for "token system"
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Showing 67 open source projects for "token system"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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claude-token-efficient
One CLAUDE.md file. Keeps Claude responses terse
...The approach focuses on removing redundant explanations, overly polite language, and repeated context, which are common contributors to excessive token consumption in AI-generated responses. It is particularly useful in high-volume or agent-based workflows where output tokens accumulate quickly and significantly impact cost and latency. The system works best in iterative or automation-heavy environments where consistent formatting and brevity are more valuable than exploratory reasoning. -
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rtk
CLI proxy that reduces LLM token consumption
...By minimizing the amount of noise sent to the AI model, the tool improves reasoning quality and allows longer development sessions within the same context window. The system is implemented as a lightweight Rust binary that runs locally and integrates easily with common AI coding environments. -
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Lunary
The production toolkit for LLMs. Observability, prompt management
Lunary helps developers of LLM Chatbots develop and improve them. -
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. The model supports long-context inputs, allowing it to analyze extensive documents without chunking, which improves consistency in redaction tasks. It can run locally on standard hardware, ensuring that sensitive information never leaves the user’s environment and supporting privacy-first workflows. ... -
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Pinchtab
High-performance browser automation bridge and orchestrator
...Implemented as a small standalone HTTP server, it allows any agent or script to interact with web pages using simple API calls instead of heavyweight browser frameworks. The tool emphasizes accessibility-first snapshots that dramatically reduce token usage compared to screenshot-based approaches, making it cost-effective for large-scale automation. It launches and manages its own Chrome instance while remaining framework-agnostic, so it can be used with any language or agent system. Pinchtab also supports persistent sessions, stealth automation, and both headless and headed operation modes. ... -
6
RecursiveMAS
Offical Implementation for "Recursive Multi-Agent Systems"
...Instead of treating agents as independent units exchanging text outputs, it connects them through a shared latent computation loop, allowing internal “thought states” to be passed and refined iteratively. This recursive structure enables agents to build on each other’s intermediate reasoning, leading to deeper and more coherent solutions. The system uses a lightweight module called RecursiveLink to transfer and transform latent representations between agents, enabling seamless interaction even across heterogeneous models. It also incorporates an inner–outer loop training approach that optimizes the entire system collectively rather than tuning each agent separately. This design improves efficiency, reduces token usage, and stabilizes learning during iterative reasoning. -
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OpenMonoAgent
Terminal-native coding agent powered by local LLMs
OpenMonoAgent.ai is a self-hosted coding agent designed to run entirely on the user’s own hardware. It pairs a .NET CLI with a local llama.cpp inference server so developers can use agentic coding workflows without cloud subscriptions or per-token billing. The project emphasizes privacy, local control, and ownership of the model, compute, and project data. It includes a terminal-native workflow, built-in tools, Docker sandboxing, and code intelligence features. The system can run on CPU or GPU and is designed to auto-configure itself when possible. OpenMonoAgent.ai is best suited for developers who want a local AI development stack with no API keys, no cloud dependency, and no telemetry. -
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Oh My OpenCode Slim
Slimmed, cleaned and fine-tuned oh-my-opencode fork
Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents, each with a defined role such as orchestration, exploration, and execution, allowing tasks to be automatically delegated and completed through coordinated workflows. ... -
9
Lossless Claw
LCM (Lossless Context Management) plugin for OpenClaw
...Instead of relying on traditional sliding-window truncation or lossy summarization, it introduces a lossless architecture that preserves all historical messages while maintaining usable context within token limits. The system stores every interaction in a persistent database and incrementally summarizes older content into a hierarchical directed acyclic graph, allowing efficient compression without discarding information. This structure enables agents to dynamically reconstruct detailed context by expanding summaries when needed, effectively simulating perfect long-term memory. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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10
Claude Cognitive
Persistent context and multi-instance coordination
Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant... -
11
Claude-Mem
Claude Code plugin that automatically captures everything Claude does
...Its progressive disclosure approach intelligently injects only the most relevant context, balancing usefulness with token efficiency. Claude-Mem runs automatically in the background with no manual workflow changes required. Designed for serious developers, it transforms Claude Code into a continuously learning, project-aware coding assistant. -
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Claw Compactor
14-stage Fusion Pipeline for LLM token compression
...It addresses the challenge of finite context windows in language models by compressing or summarizing historical interactions while preserving essential information. The system works by transforming older conversation data into condensed representations that maintain continuity without exceeding token limits. This approach allows long-running agent sessions to continue operating efficiently without losing critical context. It is especially useful in autonomous workflows where agents accumulate large volumes of interaction history over time. ... -
13
Claude Code Usage Monitor
Real-time Claude Code usage monitor with predictions and warnings
Claude Code Usage Monitor is a developer-focused terminal tool that provides real-time visibility into Claude Code token consumption and session behavior. The project is designed to help users avoid unexpectedly hitting usage caps by continuously tracking token burn rate, message counts, and estimated costs during active sessions. It presents analytics through a visually rich terminal interface built with modern Python tooling, making it easy to interpret usage trends at a glance. ... -
14
Claude Code Bridge
Real-time multi-AI collaboration: Claude, Codex & Gemini
Claude Code Bridge is an open-source command-line tool designed to enable real-time collaboration between multiple AI coding assistants within a unified development environment. The system allows developers to coordinate interactions between models such as Claude, Codex, and Gemini so that they can work together on programming tasks. By maintaining persistent shared context between these models, the tool reduces redundant prompts and minimizes token usage while allowing each AI system to contribute specialized capabilities. ... -
15
Continuous Claude v3
Context management for Claude Code. Hooks maintain state via ledgers
...It also includes a layered code analysis pipeline to reduce token usage and maintain relevant context efficiently. This continuous learning environment enables workflows such as bug fixing, refactoring, planning, and exploratory investigation while minimizing the need to re-explain context manually. -
16
OpenSpace
OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving
OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also focuses on cost efficiency by reducing redundant computations and reusing successful workflows, significantly lowering token usage in repeated tasks. ... -
17
Model Context Protocol (MCP) Servers
Model Context Protocol Servers
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. -
18
abtop
Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI
abtop is a terminal monitoring tool for AI coding agents, inspired by system monitors like htop and btop. It gives users a real-time view of active Claude Code, Codex CLI, and OpenCode sessions from local process and file state. The dashboard helps developers track token usage, context window percentage, rate limits, child processes, open ports, and multiple active profiles. It is read-only, so it does not require API keys or authentication and does not control the agents it observes. abtop is especially useful for developers running several agents across projects who need quick visibility into cost, quota pressure, context growth, and orphaned processes. ... -
19
claude-devtools
A desktop app that reconstructs exactly what Claude Code did
claude-devtools is an open-source desktop observability tool designed to provide deep visibility into Claude Code sessions by reconstructing execution activity directly from local session logs. Rather than acting as a wrapper or modifying Claude Code behavior, the application passively reads the logs stored in the user’s environment and rebuilds a structured, searchable timeline of what actually occurred during each session. The tool was created to address the loss of detail in the standard... -
20
InfiAgent
Build your own Cowork, AI Scientist and other SoTA Agents
infiAgent is an open-source AI agent framework for building powerful, long-running autonomous agents capable of tackling complex tasks without collapsing under growing context or tool invocation histories. Designed as a “Multi-Level Agent” (MLA) system, it externalizes persistent state to the file system so that agents can operate over unlimited runtime without the need for token-intensive context compression, enabling workflows such as research paper drafting, experiments, coding, and document generation to run reliably. The framework uses a serial multi-agent hierarchy where specialized agents coordinate in tree-structured paths for clear task delegation and minimal tool conflicts, while batch file operations and persistent workspaces ensure reproducibility and traceability. ... -
21
DeepSeek-OCR 2
Visual Causal Flow
DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents... -
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WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper
WhisperSpeech is an open-source text-to-speech system created by “inverting” OpenAI’s Whisper, reusing its strengths as a semantic audio model to generate speech instead of only transcribing it. The project aims to be for speech what Stable Diffusion is for images: powerful, hackable, and safe for commercial use, with code under Apache-2.0/MIT and models trained only on properly licensed data. -
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DevDocs by CyberAGI
Completely free, private, UI based Tech Documentation MCP server
...This approach reduces token usage and improves the accuracy of responses generated by AI coding assistants. The platform is designed to integrate easily with modern developer tools and AI environments such as Cursor, Cline, and Claude-based workflows. It includes a user interface that allows developers to browse documentation repositories and connect them to AI systems while keeping the data private. -
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uqlm
Uncertainty Quantification for Language Models, is a Python package
UQLM is a Python library developed to detect hallucinations and quantify uncertainty in the outputs of large language models. The system implements a variety of uncertainty quantification techniques that assign confidence scores to model responses. These scores help developers determine how likely a generated answer is to contain errors or fabricated information. The library includes both black-box and white-box approaches to uncertainty estimation. Black-box methods evaluate model outputs through multiple generations or comparative analysis, while white-box methods rely on token probabilities produced during inference. ... -
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Skills Janitor
Audit, track usage, and compare your Claude Code skills
...One of its core purposes is to help developers maintain a clean and efficient skill environment, especially as the number of installed skills grows over time. The system provides a set of command-based tools that allow users to perform health checks, generate reports, and automatically fix issues such as broken or redundant skills. It also includes usage tracking by parsing conversation history, giving visibility into which skills are actively used and which are wasting resources. A notable feature is its token cost analysis, which helps developers understand how much context window space each skill consumes.
