Build Secure and Compliant AI agents and MCP Servers. YC W23

Python sandboxes for llms

Comprehensive MCP server exposing dozens of capabilities to AI agents: multi-provider LLM delegation, browser automation, document processing, vector ops, and cognitive memory systems

A security scanner for your LLM agentic workflows

A Model Context Protocol (MCP) server that provides file system context to Large Language Models (LLMs). This server enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

An MCP server to allow you to debug webpages using LLMs

MCP server that gives any LLM its own computer — managed Docker workspaces with live browser, terminal, code execution, document skills, and autonomous sub-agents. Self-hosted, open-source, pluggable into any model.

An MCP server that lets LLM agents play Civilization VI.

Open-source observability & evaluation platform for AI agents and coding agents. Trace LLMs, tools, prompts, costs & agent workflows with OpenTelemetry.

Minimal AI coding agent (~1,000 lines of Python) inspired by Claude Code. Works with any LLM. Think NanoGPT for coding agents. Formerly NanoCoder.

SRA-Bench and SR-Agents: a benchmark and toolkit for skill-retrieval-augmented LLM agents.

An MCP server for interacting with Sentry via LLMs.

CTX: a tool that solves the context management gap when working with LLMs like ChatGPT or Claude. It helps developers organize and automatically collect information from their codebase into structured documents that can be easily shared with AI assistants.

Shell and coding agent on mcp clients

Open-World Self-Evolution for LLM Agents — agents that build both their skills and their own verification signals from scratch, with no target-task supervision. (Code coming soon.)

A lightweight agent harness you bolt onto your app so an LLM can operate it — safely, and cheaply.

Let LLMs control embedded devices via the Model Context Protocol.

Centralize ESP32 related commands and simplify getting started with seamless, LLM-driven interaction and help.

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.

Multi Debugger MCP server that enables LLMs to interact with GDB and LLDB for binary debugging and analysis.

An LLM-powered, autonomous coding assistant. Also offers an MCP and ACP mode.

FuXi is a fast, self-contained AI coding agent that lives in your terminal — edit code, run commands, and drive tools, with cost-aware routing across LLM providers.

A Model Context Protocol (MCP) server that enables LLMs to run ANY code safely in isolated Docker containers.