342 boosters for "agents" — open source, verified from GitHub, ready to install
"name": "dotnet-claude-kit", "description": "The definitive Claude Code companion for .NET developers. 47 skills, 10 agents, 16 commands, 10 rules, 5 templates, 15 MCP tools, 7 hooks for modern .NET 10 / C# 14.", "name": "Mukesh Murugan",
17 Google Maps tools for AI agents — geocode, search, directions, weather, air quality, map images via MCP server or standalone CLI
Tableau MCP Server enables AI agents to directly access, visualize, and analyze Tableau data within Claude, helping teams explore business intelligence without switching tools. Developers and data analysts benefit from seamless integration of Tableau dashboards and datasets into AI-powered workflows.
Empirica is a system prompt that adds epistemic measurement, RAG grounding, and calibration gates to AI agents to reduce hallucinations and improve reliability in code generation workflows. It's designed for developers building AI-native applications who need measurable confidence in agent outputs.
"version": "0.10.0", "description": "AI agents on autopilot - define in markdown, run on cron, CI/CD, or serverless", "license": "Apache-2.0",
Recall MCP Server enables persistent, cross-session memory for Claude and AI agents through Redis/Valkey or managed cloud hosting, allowing AI systems to retain and retrieve context across conversations. Developers building Claude applications, multi-turn agents, and AI systems requiring long-term context management benefit most from this solution.
Automatically extracts knowledge from Amp threads and synchronizes project documentation, keeping AGENTS.md and other docs up-to-date after epics and major work. Ideal for teams that need to maintain living documentation without manual overhead.
Execute the release automation script with auto-confirmation for Claude Code. PROJECTROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD") cd "$PROJECTROOT" && bash .claude/scripts/release.sh $ARGUMENTS --yes
"name": "tensorlake", "description": "Tensorlake SDK for agent sandboxes and sandbox-native orchestration. Use when building AI agents that need sandboxed execution environments, isolated tool calls, or durable workflow orchestration.", "author": "TensorLake",
You are guiding the developer through strict Test-Driven Development. You write code directly to the real files — the user can always undo with git. Pause only when the user's input is needed, not at every step. 1. Determine the input type: 2. Detect the language and test framework from the project.
<summary >🌐 Language</summary> <div align="center"> <a href="https://openaitx.github.io/view.html?user=wshobson&project=agents&lang=en">English</a>
Sub-Agents enables parent agents to delegate specialized tasks to child agents with independent prompts, tools, and providers, allowing developers to build modular, hierarchical AI systems that solve complex multi-step problems.
"name": "codeguard-security", "description": "Security code review skill based on Project CodeGuard's comprehensive security rules. Helps AI coding agents write secure code and prevent common vulnerabilities.", "name": "Project CodeGuard",
Memelord is a persistent memory system for AI coding agents that uses vector search and reinforcement learning to help agents learn from past interactions. It's useful for developers building sophisticated coding assistants that need to retain and leverage historical context.
A local SQLite-based command-line task board for AI agents and developers to manage multi-step coding tasks, track progress, and coordinate work across sessions without external dependencies. Ideal for breaking down complex implementations into trackable subtasks with comments and checklists.
uni-cli is a unified command-line interface that enables AI agents to seamlessly interact with 25+ services (messaging, productivity, research, utilities) through a consistent pattern. Developers and AI builders benefit from simplified multi-service integration without learning individual APIs.
Automates GitHub issue triage and fixing by fetching issues, spawning AI sub-agents to implement solutions, opening PRs, and handling review feedback—ideal for maintainers and teams managing high-volume bug backlogs.
"name": "prism-mcp-server", "mcpName": "io.github.dcostenco/prism-mcp", "description": "The Mind Palace for AI Agents — persistent memory (SQLite/Supabase), behavioral learning & IDE rules sync, multimodal VLM image captioning, pluggable LLM providers (OpenAI/Anthropic/Gemini/Ollama), OpenTelemetry
Heuristic scoring (no AI key configured).
"name": "@ticktockbent/charlotte", "description": "Token-efficient browser MCP server — structured web pages for AI agents, not raw accessibility dumps", "main": "dist/index.js",
A concurrent sub-agent executor that transparently parallelizes independent tool calls in agentic workflows, enabling faster multi-step operations without explicit LLM coordination. Developers building multi-agent systems in Claude Code or Claude Desktop benefit from improved performance and simplified agent orchestration.
"name": "@paretools/bazel", "version": "0.16.1", "mcpName": "io.github.Dave-London/pare-bazel",
"name": "@paretools/jvm", "version": "0.16.1", "mcpName": "io.github.Dave-London/pare-jvm",
PSI is a structured Plan-Spec-Implement workflow that guides developers through documentation-first development with test-driven implementation. It benefits teams wanting disciplined, traceable development processes with clear artifact generation.
