Best tools for Agentic Development

Swiss-army MCP server for local system automation

DesktopCommanderMCP is a general-purpose MCP server that gives AI agents the ability to execute local programs, read and write files, search the filesystem, and edit text files. It acts as a comprehensive local system actuator, enabling coding agents to interact with the development environment beyond just code editing.

Lifelike AI voice generation, cloning, and voice agents

ElevenLabs is an AI voice platform for text-to-speech, voice cloning, and conversational AI agents, built on models like Multilingual v2 and the low-latency Flash v2.5 and Turbo v2.5. Developers call its API to generate lifelike narration, clone voices from short audio samples, dub content across 30+ languages, add sound effects, and deploy real-time voice agents for customer service, IVR, and interactive apps, with SDKs for Python, JavaScript, and more.

Prompt engineering framework treating prompts as versioned Python functions

Ell is a prompt engineering library that treats LLM prompts as versioned, testable Python functions rather than opaque strings. Built by ex-OpenAI researcher William Guss, it provides automatic prompt versioning with content-addressable hashing, a local TensorBoard-like studio for visualizing prompt evolution, and structured output support via Pydantic. 5,800+ GitHub stars, MIT licensed. Designed for teams who want to version-control and systematically improve their prompts over time.

Agent harness performance system with 30+ agents and 136 skills

Everything Claude Code is a comprehensive agent harness performance optimization system providing 30 specialized agents, 136 skills, 60 commands, and automated hook workflows for AI-assisted development. Born from an Anthropic hackathon winner and evolved over 10+ months of intensive daily use, it works across Claude Code, Codex, Cursor, and OpenCode with built-in security scanning via AgentShield, continuous learning, and research-first development patterns.

MCP gateway and integration catalog for AI agents

Executor is an MIT-licensed integration layer and MCP gateway for AI agents. It gives Claude Code, Cursor, Codex, and other MCP-speaking clients one endpoint for connected OpenAPI specs, GraphQL APIs, MCP servers, Google Discovery sources, and custom JavaScript tools, with local, cloud, and self-hosted deployment options for teams centralizing tool access.

Zero-config conversion of FastAPI endpoints into MCP tools

FastAPI-MCP automatically converts existing FastAPI endpoints into Model Context Protocol tools with zero configuration. With 11,700+ GitHub stars, it is the most popular MCP integration layer, enabling thousands of FastAPI developers to make their APIs accessible to AI agents like Cursor and Claude through the MCP standard.

Turn a Figma design system into a programmable API for AI assistants

Figma Console MCP is open-source design-system infrastructure that exposes Figma to AI assistants through MCP. It supports structured extraction, design creation and editing, debugging, accessibility audits, and bidirectional design-token workflows across local, remote read-only, and paired cloud modes; it is not a generic one-click Figma-to-code exporter.

Visual workflow builder by ByteDance

FlowGram is an open-source visual workflow and flowchart editor framework developed by ByteDance for building node-based workflow applications. It provides a React-based canvas with drag-and-drop node creation, configurable edge routing, zoom and pan controls, and a plugin architecture for extending functionality. FlowGram supports both fixed layout and free-form canvas modes, making it suitable for building AI agent pipelines, data processing flows, and automation builders.

Natural language scripting for LLM-system interaction

GPTScript is an Apache 2.0 licensed framework with 3,300+ GitHub stars that enables natural language scripting where LLMs interact with local systems, APIs, and tools through simple prompt definitions. It supports multiple model providers including OpenAI-compatible APIs and local models, providing a lightweight approach to building AI agents that can execute CLI commands, call APIs, and process files.

Meta-prompting and context engineering system for Claude Code agents

GSD is a meta-prompting, context engineering, and spec-driven development system designed for Claude Code and compatible AI coding agents. With over 46,000 GitHub stars, it implements a structured four-phase workflow of Discuss, Plan, Execute, and Verify to combat context rot in long AI coding sessions. The system uses multi-agent orchestration with persistent file-based memory.

MCP server for AI-powered reverse engineering

GhidraMCP is an MCP server that enables LLMs to autonomously perform reverse engineering tasks through NSA's Ghidra disassembly framework. It exposes binary analysis capabilities like decompilation, function listing, cross-references, and symbol analysis as MCP tools, letting AI assistants generate malware reports and analyze compiled binaries.

Instant MCP server for any GitHub repository

GitMCP is a free, open-source remote MCP server that transforms any GitHub repository or GitHub Pages site into an AI-accessible documentation hub. Just replace github.com with gitmcp.io in any repo URL to give AI assistants grounded context about that project — eliminating code hallucinations with zero configuration required.

Pull Requests as a Service with AI + developers

GitStart is a YC-backed platform that delivers merge-ready pull requests by combining AI coding agents with human developer oversight. Teams assign sprint-sized tickets and the AI Ticket Studio converts vague requirements into well-scoped specs, then hybrid agents generate production-ready code through a five-stage quality process with a 98% merge rate reported across customer teams.

MCP server directory and gateway

AI gateway and model management platform that provides a unified API for accessing multiple LLM providers (OpenAI, Anthropic, Google, Mistral, and more) through a single endpoint. Features model routing, cost tracking, usage analytics, rate limiting, and API key management across providers. Simplifies multi-provider AI integration by handling authentication, billing, and failover in one place. Useful for teams evaluating multiple models or building provider-agnostic AI applications.

Agent Development Kit by Google

Google's open-source framework for building AI agents with Gemini models. Supports multi-agent orchestration, tool use, and deployment to Vertex AI or Cloud Run. Provides a structured approach to agent development with built-in evaluation, testing, and monitoring capabilities, making it the official path for teams building agent systems within the Google Cloud ecosystem.

MCP server for secure database tooling with AI agents

Google GenAI Toolbox is an open-source MCP server from Google that specializes in easy, fast, and secure database tools for AI agents. It provides structured database access through the Model Context Protocol, enabling agents to query, inspect schemas, and manage data across supported databases with built-in security controls.

Build real-time temporal knowledge graphs for AI agents

Graphiti is an open-source Python framework by Zep for building temporally-aware knowledge graphs for AI agents. It continuously integrates conversations, business data, and external information into queryable graphs with bi-temporal tracking. The hybrid retrieval combines semantic search, BM25 keywords, and graph traversal for sub-300ms queries without LLM calls at retrieval time.

Modular AI agent framework with off-prompt data

Griptape is an open-source Python framework for building AI agents and workflows with a focus on modularity and enterprise-grade off-prompt data handling. It separates predictable pipeline logic from unpredictable LLM interactions, providing structures for sequential and parallel task execution with built-in memory management and tool integration.

Validate and structure LLM outputs with composable Guards

Guardrails AI is an open-source Python and JavaScript framework for validating and structuring LLM outputs using composable Guards built from a Hub of pre-built validators. It handles structured data extraction with Pydantic models, content safety checks including toxicity, PII detection, competitor mentions, and bias filtering, plus automatic re-prompting when validation fails. The Guardrails Hub offers dozens of validators from regex matching to hallucination detection via LLM judges.

Constrained generation that guarantees valid LLM outputs every time

Guidance is Microsoft's structured generation library that enforces output constraints directly within LLM decoding. It supports JSON schemas, regex patterns, grammars, and interleaved generation-and-control flow to guarantee valid outputs from any compatible model. Works with local models via llama.cpp, Transformers, and remote APIs including OpenAI and Anthropic. Eliminates retry loops and post-processing for structured data extraction.

NLP and RAG pipeline framework by deepset

Haystack is an open-source AI orchestration framework by deepset for building production-ready LLM applications with explicit control over retrieval, routing, memory, and generation pipelines. Its component-based architecture lets developers chain specialized pieces into branching, looping pipelines for semantic search, RAG, QA, and autonomous agents. Integrates with OpenAI, Anthropic, Mistral, Cohere, Hugging Face, Azure, AWS Bedrock, and major vector stores.

AI-native API gateway by Alibaba with MCP server hosting and LLM routing

Higress is an open-source AI-native API gateway developed by Alibaba that combines traditional API management with LLM-specific capabilities like token-based rate limiting, model routing, prompt caching, and MCP server hosting. Built on Envoy and Istio, it provides enterprise-grade traffic management while natively understanding AI workload patterns including streaming responses, long-lived connections, and multi-model fallback chains.

Agent memory system that learns, not just remembers

Hindsight is an agent memory system that enables AI agents to learn from experience rather than just store conversations. It organizes memories into three biomimetic categories: World knowledge for facts, Experiences for agent events, and Mental Models for learned understanding. The system provides retain, recall, and reflect operations backed by a temporal knowledge graph with parallel retrieval strategies including semantic, keyword, graph traversal, and temporal search.

Architect agent that builds with reusable components

Hope AI by Bit Cloud is an architect agent with 18,000+ GitHub stars on the Bit platform that builds professional software using reusable components. It proposes entire software architectures, generates code with documentation and test coverage, and ensures clean component patterns, addressing the architectural integrity gap that most vibe-coding tools ignore when generating code.

HubSpot's hosted MCP server for CRM data and workflows.

HubSpot MCP Server is HubSpot's hosted remote MCP server for connecting compatible AI tools to CRM data. It uses OAuth 2.1 with PKCE through MCP auth apps, then exposes HubSpot context such as contacts, companies, deals, tickets, activities, and marketing or content objects according to user permissions, granted scopes, and sensitive-data restrictions in the account.

ACP skill definitions giving coding agents HuggingFace ML superpowers

Hugging Face Skills is the official collection of ACP skill definitions that give AI coding agents access to HuggingFace ML capabilities. The 13 skills cover LLM fine-tuning with TRL, vision model training, dataset management, model evaluation, and cloud job submission on HF infrastructure. Compatible with Claude Code, Codex, Gemini CLI, and Cursor via a single npx command.

Structured LLM outputs with validation

Instructor is the most popular Python library for extracting structured, validated data from large language models, with over 3 million monthly downloads and ports across Python, TypeScript, Go, Ruby, Elixir, and Rust. It uses Pydantic models to define output schemas and automatically handles validation, retries, and error correction when the LLM output does not match. Instructor patches existing client libraries instead of replacing them, preserving full access to the underlying API.

Intercom's remote MCP server for support and Help Center context.

Intercom MCP Server is Intercom's hosted remote MCP server for connecting AI tools to Intercom workspace data. It supports the recommended Streamable HTTP endpoint, OAuth or bearer-token authentication, and tools for conversations, contacts, companies, and Help Center article workflows, with access limited by token permissions and Intercom workspace policy.

BEAM/Elixir-native framework for durable multi-agent systems

Jido is an Elixir-native AI agent framework that leverages the BEAM virtual machine's concurrency and fault-tolerance for building durable, distributed multi-agent systems. It provides primitives for agent lifecycle management, skill composition, and message-based coordination. Designed for teams running Elixir in production who need agent capabilities. Apache-2.0 with 1,600+ GitHub stars.

JavaScript framework for building and visualizing multi-agent workflows on a Kanban board

KaibanJS is an MIT-licensed JavaScript framework for defining AI agents, tasks, tools, and teams, then orchestrating their work through a Kanban-inspired runtime and visual board. It can run inside Node.js, React, or Next.js projects, supports custom UIs and headless workflows, and provides real-time task-state visibility for multi-agent applications.

Control plane for autonomous AI agents

Keycard is the control plane for autonomous agents, providing identity verification, policy enforcement, and scoped access management. Resolves agent identity, enforces security policies, and issues time-limited resource-specific access tokens. Provides full visibility into every agent action with drift detection, automatic remediation, and integrations with Datadog, Linear, GitHub, and other services for agent-driven incident response and security operations.

Spec-driven coding subscriptions for Kiro IDE/CLI

Kiro Plans refers to the pricing and subscription structure for AWS's Kiro IDE, ranging from a perpetual free tier to enterprise-grade Power plans with varying levels of AI-assisted requests. Pricing distinguishes between two interaction types: spec requests initiated from structured task workflows, and vibe requests for chat-based coding assistance. Designed to scale from individual developers to professional teams building production software.

MCP integration platform for agent tool use at scale

Klavis AI is an Apache-2.0 MCP integration platform for teams connecting AI agents to external SaaS tools and APIs. The public repo and official docs position it as infrastructure for reliable tool access at scale, so it fits teams that want reusable MCP connectors without treating every integration as a one-off script or custom OAuth maintenance project.

Kotlin-native AI agent framework by JetBrains with MCP support

Koog is JetBrains official Kotlin-native framework for building predictable, fault-tolerant AI agents. It provides structured agent workflows with MCP protocol support, type-safe tool definitions, and deterministic execution patterns designed for JVM production environments. As the first production-grade Kotlin agent framework, it fills the gap in a JVM ecosystem dominated by Python-based alternatives and integrates naturally with existing Kotlin and Java backend infrastructure.

RAG-based document QA with multi-user support and agent reasoning

Kotaemon is an open-source RAG-powered document question-answering interface backed by Cinnamon AI. It supports multi-user workspaces with access controls, advanced retrieval pipelines including hybrid search and knowledge graph extraction, and agentic reasoning for complex multi-step queries. The web UI handles PDFs, Office documents, and images with citations pointing to exact source passages, making it suitable for both individual research and team knowledge management.

GenAI-powered test agent with natural language test authoring

KaneAI is LambdaTest's GenAI-powered test automation agent that creates, evolves, and debugs tests from natural language descriptions. It generates test scripts in multiple frameworks including Selenium, Playwright, and Cypress from plain English instructions. Features intelligent test maintenance that automatically updates tests when application UI changes and two-way editing between natural language and code.

Visual framework for building multi-agent AI apps

LangFlow is an open-source visual framework for building multi-agent AI apps with drag-and-drop. Built on LangChain, it lets developers compose chains, agents, and RAG pipelines by connecting modular components visually. Features real-time interaction, Python customization, one-click deployment, and export to LangChain code. Supports all major LLM providers, vector stores, and tools. With 146K+ GitHub stars, it bridges visual prototyping and production deployment.

Multi-agent programming framework inspired by the Actor model

Langroid is a lightweight Python framework from CMU and UW-Madison researchers for building LLM applications using a multi-agent programming paradigm inspired by the Actor Framework. Agents are first-class citizens that encapsulate LLM state, vector stores, and tools, then collaborate via message passing through hierarchical task delegation. With 3,900+ GitHub stars, Langroid works with any LLM provider and does not depend on LangChain or other frameworks.

Sentry-style observability for AI agent conversations

Latitude is an agent observability platform for teams that need to inspect LLM traces, conversations, issues, and evaluation feedback in one workflow. Its public repo and docs position it as a Sentry-style monitor for AI agents, with semantic search, issue detection, annotations, MCP-assisted fixes, and cloud or self-hosted deployment paths for production debugging.

Twelve-lesson curriculum for building AI coding agents from scratch

Learn Claude Code is a comprehensive educational framework with 12 structured lessons teaching AI coding agent construction from first principles. With over 46,000 GitHub stars and 7,000 forks, it provides complete runnable Python implementations progressing from a 50-line bash agent to a 550-line skills agent with modular extensibility and subagent orchestration.

Memory-first coding agent that learns over time

Letta Code is a memory-first CLI coding agent that persists across sessions and improves over time. Unlike stateless tools like Claude Code or Codex, it works with long-lived agents remembering your codebase, preferences, and past interactions. Model-agnostic supporting Claude, GPT, Gemini, and more. Features git-backed context repositories, skill learning from experience, sleep-time reflection, and subagent orchestration. #1 model-agnostic OSS harness on Terminal-Bench.

Open-source real-time voice, video, and AI agent infrastructure

LiveKit is an open-source WebRTC infrastructure platform for building real-time voice, video, and data applications. It powers ChatGPT Advanced Voice Mode and serves as the foundation for AI agent voice interactions. LiveKit provides server-side SDKs for Go, Python, Node.js, and Rust alongside client SDKs for every major platform. The Agents framework lets developers build voice-enabled AI assistants with speech-to-text, LLM processing, and text-to-speech pipelines in Python or Node.js.

Community self-hosted MCP server for Jira and Confluence (Python)

MCP Atlassian is a community-built, self-hosted Python MCP server (sooperset/mcp-atlassian) that connects AI coding agents to Jira and Confluence using API tokens or personal access tokens. It runs on your own infrastructure and supports both Cloud and Server/Data Center deployments — a flexible alternative to Atlassian's official remote MCP server when you need on-prem control, custom auth, or self-managed configuration.

IBM-backed ContextForge gateway for federating MCP, A2A, REST, and gRPC APIs

MCP Context Forge is IBM’s Apache-2.0 ContextForge project for operating a gateway, registry, and proxy across MCP servers, A2A agents, REST APIs, and gRPC services. It centralizes discovery, authentication, policy controls, federation, and observability, with deployment paths through PyPI, Docker, and Kubernetes.

Official debugger for MCP server development

MCP Inspector is the official interactive developer tool from the Model Context Protocol team for testing, debugging, and validating MCP servers. It provides a visual interface to inspect available tools, test transport configurations, export configs for different clients, and verify protocol compliance during MCP server development.

Anthropic's open standard for connecting AI models to tools and data

Model Context Protocol (MCP) is Anthropic's open standard that defines how AI models communicate with external tools, resources, and data sources. Provides a universal client-server architecture for connecting LLMs to any API or service through standardized tool definitions, resource access, and prompt templates. Rapidly adopted across the AI industry as the interoperability standard for AI tool integration.

Community MCP server registry

Community-curated directory of Model Context Protocol (MCP) servers that extend AI assistants like Claude with real-world capabilities — file access, database queries, API integrations, browser control, and more. Lists servers organized by category (developer tools, data, productivity) with installation instructions and compatibility info. Helps developers discover and connect MCP servers to their AI workflows. Essential resource for the growing MCP ecosystem.

Open-source MCP server for database access

MCP Toolbox for Databases is an open-source MCP server by Google that connects AI agents to databases through a managed control plane. It handles connection pooling, authentication, and tool distribution, letting developers integrate database tools in under 10 lines of code. Supports PostgreSQL, MySQL, BigQuery, AlloyDB, Snowflake, MongoDB, Redis, ClickHouse, Neo4j, and more with ready-to-use toolsets for Claude Code, Gemini CLI, and other MCP clients.