tools for working with LLMs
llm tools
Main client for working with LLM tools hosted on the Agentic platform.
LLM tools (recall, lookup, graph query) for Memo cognitive memory system
CLI and library for LLM tools
LLM tools app for frontend medical practitioners to use A.I
Pi extension that generates LLM tools from any OpenAPI/Swagger URL.
A NodeJS RAG framework to easily work with LLMs and custom datasets
LLM tools used in production at Dexa, with a focus on real-world RAG.
Integrated terminal panel for pi coding agent — persistent PTY shell, colored overlay, LLM tools
Docusaurus theme that adds a Copy page toolbar button to every doc page for LLM tools
Useful util functions when extending the embedjs ecosystem
Pi extension package that bridges an installed grepai CLI into Pi slash commands and LLM tools
MCP server for Minecraft mod debugging - launch, download, and run Minecraft through LLM tools via stdio
Interfaces for extending the embedjs ecosystem
Minimal, MCP-compliant framework for LLM tools, scripting, and automation.
LLM tools for API discovery from .mind spec files
MCP server for the numcal date and time calculator. Lets LLM tools like Claude Code, Claude Desktop, and Cursor get deterministic date math via natural-language queries.
Web page loader for embedjs
A scalable tools or functions orchestration SDK for LLM agents using OpenAI's /v1/responses API with memory, hooks, and tool planning support. Alternative of MCP for LLM tools orchestration.
Add LibSQL support to embedjs
Enable usage of OpenAI models with embedjs
Zero-dependency Gemini function-calling schemas and capability-scoped tool injection for edge AI agents. Works in Node.js, browser, and React Native (Hermes).
An npx-runnable MCP server for google-slides-llm-tools, allowing interaction with Google Slides via clients like Claude or Cursor.
Unified API for AI.
Framework-agnostic Rust tool definitions for LLM agents
Anthropic Messages API provider for the llm-cmd toolkit
A CLI tool for interacting with LLMs (OpenAI, Anthropic) via a unified interface
Core traits, types, and streaming primitives for the llm-cmd LLM toolkit
OpenAI Chat API provider for the llm-cmd toolkit
JSONL conversation log storage for the llm-cmd toolkit
Allow Rust functions to be called by LLMs
Proc macros for llm-tool (#[llm_tool] attribute)
Find markers in your files and replace them with LLM-generated content
Phase 80.1 — autoDream fork-style memory consolidation (KAIROS port)
A package manager for coding agent skills
liter-llm is a universal LLM API client with a Rust core and native Ruby bindings via Magnus. Provides a unified interface for streaming completions, tool calling, and provider routing across 142+ LLM providers. Rust-powered.
A tool that uses LLM to automatically fix errors detected by static analysis tools (such as RuboCop).
PrReview collects PR data from GitHub (description, commits, comments, linked issues, and code changes) and formats it as XML. Paste this XML into any LLM like ChatGPT or Claude to get helpful code reviews.
Ruby-native LLM agent framework with provider adapters (Anthropic, OpenAI, Google), tool calling, streaming, and session persistence.
A Ruby gem for building AI tools for large language models using a simple domain-specific language.
Register JSON-schema tools and let an LLM handle intent, slot-filling, and tool calls safely.
Drop-in Rails engine to register JSON-schema tools, let an Llm fill missing fields, validate input, and execute handlers safely.
LLM Bench is a Ruby gem that allows you to benchmark and compare the performance of different Large Language Model providers and APIs. It supports both OpenAI and Anthropic-compatible API formats, provides parallel execution, and includes continuous tracking capabilities with CSV export.
Productivity boosting tools powered by LLMS
LLMs::Tool provides a simple DSL for defining tools that can be serialized to the correct JSON schema to be used with LLM systems
Ruby chain tools to work with LLMs
Ruby AI Agents SDK enables creating complex AI workflows with multi-agent orchestration, tool execution, safety guardrails, and provider-agnostic LLM integration.
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