Best Artificial Intelligence Software for Claude Code - Page 7
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Compare the Top Artificial Intelligence Software that integrates with Claude Code as of July 2026 - Page 7
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This a list of Artificial Intelligence software that integrates with Claude Code. Use the filters on the left to add additional filters for products that have integrations with Claude Code. View the products that work with Claude Code in the table below.
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1
Claude Computer Use
Anthropic
Claude Computer Use is a feature that allows Claude to interact directly with your computer to complete tasks. It enables the AI to click, type, open applications, and navigate files just like a human user. The system prioritizes using built-in connectors, but can fall back to browser navigation or full screen interaction when needed. It can perform tasks such as compiling reports, filling spreadsheets, and testing applications. Users must grant permission before Claude accesses any application, ensuring control over what it can do. The feature includes safeguards to reduce risky actions and protect sensitive data. Overall, Claude Computer Use extends AI capabilities beyond chat into real-world task execution on your device. -
2
Claude Opus 4.1
Anthropic
Claude Opus 4.1 is an incremental upgrade to Claude Opus 4 that boosts coding, agentic reasoning, and data-analysis performance without changing deployment complexity. It raises coding accuracy to 74.5 percent on SWE-bench Verified and sharpens in-depth research and detailed tracking for agentic search tasks. GitHub reports notable gains in multi-file code refactoring, while Rakuten Group highlights its precision in pinpointing exact corrections within large codebases without introducing bugs. Independent benchmarks show about a one-standard-deviation improvement on junior developer tests compared to Opus 4, mirroring major leaps seen in prior Claude releases. -
3
Sculptor
Imbue
Sculptor is a coding agent environment from Imbue that embeds software engineering practices into an AI-augmented development workflow; it runs your code in sandboxed containers, spots issues (e.g., missing tests, style violations, memory leaks, race conditions), and proposes fixes that you can review and merge. You can launch multiple agents in parallel, each operating in its isolated container, and use “Pairing Mode” to sync an agent’s branch into your local IDE for testing, editing, or collaboration. Changes go back and forth in real time. Sculptor also supports merging agent outputs while flagging and resolving conflicts, and includes a Suggestions feature (beta) to surface improvements or catch problematic agent behavior. It preserves full session context (code, plans, chats, tool calls) so you can revisit prior states, fork agents, and continue work across sessions. -
4
Claude Opus 4.5
Anthropic
Claude Opus 4.5 is Anthropic’s newest flagship model, delivering major improvements in reasoning, coding, agentic workflows, and real-world problem solving. It outperforms previous models and leading competitors on benchmarks such as SWE-bench, multilingual coding tests, and advanced agent evaluations. Opus 4.5 also introduces stronger safety features, including significantly higher resistance to prompt injection and improved alignment across sensitive tasks. Developers gain new controls through the Claude API—like effort parameters, context compaction, and advanced tool use—allowing for more efficient, longer-running agentic workflows. Product updates across Claude, Claude Code, the Chrome extension, and Excel integrations expand how users interact with the model for software engineering, research, and everyday productivity. Overall, Claude Opus 4.5 marks a substantial step forward in capability, reliability, and usability for developers, enterprises, and end users. -
5
Claude Security
Anthropic
Claude Security is an AI-powered cybersecurity tool designed to help organizations scan their codebases and fix vulnerabilities efficiently. It analyzes code to identify potential security issues and validates findings to reduce false positives. The platform provides clear explanations of each vulnerability, including severity and potential impact. It also generates suggested patches that developers can review and approve before implementation. Claude Security integrates directly into existing workflows, making it easy to adopt without complex setup. It supports scanning entire repositories or specific sections based on user needs. The system helps streamline the process from detection to resolution in a single workflow. By automating security analysis, Claude Security improves efficiency and strengthens software protection. -
6
nono
Always Further
nono is an open source, kernel-enforced sandbox for AI coding agents and LLM workloads. Unlike policy-based guardrails that intercept and filter operations, nono uses OS security primitives — Landlock on Linux and Seatbelt on macOS — to make unauthorised operations structurally impossible at the syscall level. Wrap any AI agent — Claude Code, OpenCode, OpenClaw, or any CLI process — with a single command. nono applies default-deny filesystem access, blocks destructive commands (rm, dd, chmod, sudo), isolates credentials and API keys, and cascades all restrictions to child processes. No escape mechanism exists once restrictions are applied. Built-in profiles get you running in seconds. Secrets inject securely from the system keystore and are zeroised on exit. Audit logging, atomic rollbacks, and Sigstore-attested policy signing are on the roadmap. Apache 2.0. From the creator of Sigstore. -
7
Claude Dispatch
Anthropic
Claude Dispatch is a feature that allows users to assign tasks to Claude from anywhere and have them completed on their desktop automatically. It enables continuous conversations across devices, letting users start a task on mobile and receive results once the work is done. This helps streamline workflows by turning Claude into an always-available task executor. -
8
Orthogonal
Orthogonal
Orthogonal provides specialized development services focused on building and scaling Software as a Medical Device (SaMD) and connected medical device systems, combining modern engineering practices with strict regulatory compliance. Their approach spans the full product lifecycle, including user experience design, human factors integration, requirements definition, risk analysis, Agile software development, and verification and validation to ensure both functionality and safety. It emphasizes the use of Agile methodologies adapted to regulated environments, enabling iterative development, faster feedback cycles, and continuous improvement while maintaining compliance with standards such as FDA, EU MDR, and ISO frameworks. Orthogonal supports the development of mobile, web, and desktop applications, cloud-based systems, AI algorithms, and SDKs that integrate with third-party platforms, allowing medical devices to connect, process data, and deliver insights. -
9
Agentation
Agentation
Agentation is a visual feedback tool designed for AI coding workflows that transforms user interface annotations into a structured, machine-readable context that AI agents can understand and act on. It allows users to click directly on elements within a live application, add notes or feedback, and generate formatted output that can be pasted into AI tools such as Claude Code, Cursor, or other coding agents. This output includes precise technical details such as CSS selectors, source file paths, component hierarchy, and computed styles, enabling agents to locate and modify the exact part of the codebase without ambiguity. By capturing both visual context and user intent, Agentation eliminates the need to describe UI issues in natural language, reducing misinterpretation and improving the accuracy of AI-generated fixes. It operates through an interactive overlay that highlights elements on hover and supports structured annotations. -
10
XHawk
XHawk
XHawk is an AI-native developer platform designed to transform scattered code, documentation, and team knowledge into a unified, searchable system of context. It captures every coding session, commit, and decision, automatically organizing them into a living knowledge graph that evolves with the codebase. It converts code changes and development activity into structured, indexed documentation, ensuring that knowledge stays synchronized with every pull request and eliminating gaps between code and documentation. It provides a shared context layer that enables both humans and AI coding agents to plan, code, review, test, and operate systems with a consistent understanding, reducing hallucinations caused by missing context. XHawk includes features such as session intelligence, where every git commit syncs session history and agent reasoning, creating a permanent, searchable record of how software is built. -
11
Journey
Journey
Journey is a registry platform designed for discovering, installing, and sharing reusable AI agent workflow kits that give agents new capabilities instantly. It allows users to browse a library of pre-built workflows, known as “kits,” which can be installed directly into AI agents through a simple command or prompt, eliminating the need for manual setup or complex configuration. Each kit represents a complete, portable workflow that bundles together system prompts, behavioral instructions, tool integrations, model preferences, and structured task sequences, enabling agents to execute consistent, repeatable processes across different environments. It supports integration with multiple agent systems such as Claude, Cursor, Codex, and other compatible tools, making it flexible and adaptable for various development setups. Journey also provides tools for teams to manage workflows collaboratively, including version control, permission management, and centralized coordination. -
12
Lunagraph
Lunagraph
Lunagraph is an AI-powered design canvas that allows users to create user interfaces directly using real code instead of abstract design layers, combining visual design and development into a single workflow. It enables designers, developers, product teams, and other collaborators to build interfaces using actual HTML, CSS, and React components, ensuring that what is created on the canvas is exactly what ships in production. It eliminates traditional handoff processes by allowing users to design directly with the “raw material” of code, avoiding translation errors and inconsistencies between design files and implementation. It integrates an AI assistant, powered by Claude Code, that works alongside the canvas to help refactor components, generate variations, apply design systems, and make large-scale changes while maintaining the full context of the project, including the codebase and design assets. -
13
Simaril
Simaril
Silmaril is a self-healing prompt injection defense designed to protect AI systems from increasingly complex, multi-step attacks that traditional guardrails fail to stop. It operates by wrapping inference calls and evaluating whether an execution sequence is leading toward a harmful outcome, rather than simply filtering inputs. It uses a multihead classifier that analyzes user intent, application context, and execution states together, enabling it to detect indirect injection, multi-turn attack chains, context poisoning, and tool abuse before damage occurs. Silmaril continuously strengthens its defenses through autonomous threat hunting agents that probe systems, discover vulnerabilities, and generate synthetic training data from real attack scenarios. These insights are used to retrain the model automatically, deploying updated protections in under an hour and propagating anonymized defenses across all deployments. -
14
Hyper
Hyper
Hyper is an AI-powered internal developer platform designed to help enterprise teams build custom software, internal tools, and applications faster, smarter, and at scale. It acts as a “first-mile” engine for software development, enabling organizations to transform structured business logic into fully functional, developer-owned applications using AI-native scaffolding. It emphasizes speed and sovereignty, allowing teams to create secure and scalable solutions in days while maintaining full control over their systems without reliance on external vendors. Hyper is built to replace fragmented workflows and disposable prototypes with a cohesive architecture that mirrors an organization’s internal structure, standards, and processes. It introduces a system of context where interactions, memory, and business logic are structured in a way that allows AI agents not just to retrieve data but to reason over it and participate directly in execution. -
15
Lanes
Lanes
Lanes is a local-first desktop application designed to help developers manage and interact with AI coding agents in a private, secure environment where all work remains on the user’s machine. It operates on the principle that sensitive development data, such as source code, terminal activity, prompts, AI responses, and project configurations, should never leave the local device, ensuring full confidentiality and control. It integrates with third-party AI coding agents and CLI tools like Codex, Claude Code, or Gemini CLI, but does not act as an intermediary; instead, all communication occurs directly between the user’s machine and those services. This architecture allows developers to use powerful AI tools while maintaining strict data privacy and ownership. Lanes supports account management through simple authentication and collects only minimal, anonymous telemetry data, such as feature usage patterns, session duration, and crash reports, to improve performance. -
16
Monid
Monid
Monid is an agent-native router that helps AI agents discover, access, and pay for external tools through a single unified skill. The platform gives agents access to more than 200 tools across dozens of providers without requiring separate API keys, subscriptions, or manual setup for each service. Monid allows an agent to search for the right endpoint using natural language, compare providers, understand pricing, and execute tool calls through one shared balance. Its pay-per-call model helps users avoid seat-based subscriptions and only pay for the specific tool usage their agents need. The platform supports MCP-compatible agents and can be used in environments such as web chats, IDEs, terminals, and agent frameworks. Monid normalizes provider responses into structured JSON so agents can compare results and route by quality rather than API differences. -
17
Agensi
Agensi
Agensi is a curated marketplace for AI agent skills. Every skill is security-scanned, works across 20+ agents (Claude Code, Codex CLI, Cursor, Gemini CLI, Copilot, and more), and comes from an accountable creator. Skills are one-time purchases. Buy once, own forever. No subscriptions, no license keys. All skills use the open SKILL.md standard, so one purchase works across every compatible agent. Every submission goes through an 8-point automated security scan covering prompt injection, data exfiltration, dangerous commands, secret detection, and obfuscated code. Creators keep 80% of each sale with instant Stripe payouts. Downloads are buyer-fingerprinted for IP protection. Agensi also offers a MCP subscription ($9/month or $90/year) that gives AI agents live access to the full catalog. Your agent connects to Agensi via MCP, searches available skills, and loads the right one mid-conversation. No downloads, no file management. New skills are available the moment they go live. -
18
Straiker
Straiker
Straiker is an AI-native security platform built specifically to protect enterprise AI applications and autonomous agents, focusing on the emerging risks of “agentic AI” systems that interact with tools, APIs, and sensitive data. It provides full visibility and control across the entire AI stack by analyzing behavioral signals from models, prompts, tools, identities, and infrastructure, enabling real-time detection and prevention of AI-specific threats such as prompt injection, privilege escalation, data exfiltration, and malicious tool usage. It combines continuous discovery, adversarial testing, and runtime protection through core components like Discover AI, Ascend AI, and Defend AI, which together identify all active agents, simulate attacks to uncover vulnerabilities, and enforce real-time safeguards during execution. Its multi-layered architecture captures deep contextual signals across user interactions, networks, and agent workflows. -
19
SubQ
Subquadratic
SubQ is a large language model developed by Subquadratic, designed specifically for long-context reasoning tasks. It can process up to 12 million tokens in a single prompt, allowing it to analyze entire codebases, long histories, and complex datasets at once. The model uses a sub-quadratic sparse-attention architecture that improves efficiency by focusing only on the most relevant relationships in the data. This approach reduces computational overhead while maintaining strong performance on large-scale tasks. SubQ is optimized for use cases such as software engineering, coding agents, and long-context retrieval. It delivers fast processing speeds and operates at a lower cost compared to many traditional models. Developers can access SubQ through APIs or integrate it into coding tools for enhanced workflows. Its architecture enables scalable AI reasoning without the limitations of standard transformer models. -
20
ReinforceNow
ReinforceNow
ReinforceNow is an end-to-end platform for continual learning with AI agents, built to help teams deploy, train, and repeat. It lets developers build AI agents and continuously train them on production traffic, or let Claude Code help set it up automatically. It handles reinforcement learning infrastructure, experiment orchestration, agent versioning, GPU training logic, and telemetry, so teams can focus on agent logic, data collection, and rewards. ReinforceNow supports fast LLM fine-tuning with LoRA, high-throughput training, and wide model support for open source models like Qwen, DeepSeek, and GPT-OSS. It provides advanced telemetry to evaluate, monitor, and iterate on AI agent LLM applications, with traces, rewards, experiment metrics, and training observability. Teams can train on long-horizon tasks with 32k to 1 million context size, build vertical agents for multi-turn and long-running tasks, and use rich tooling for reinforcement learning workflows. -
21
Conductor
Conductor
Conductor lets you run a team of coding agents on your Mac, giving each Claude Code or Codex agent its own isolated workspace so you can parallelize software work without losing control. Add your repo, and Conductor clones it and works entirely on your Mac. Deploy agents, and each one gets a separate git worktree where it can work independently. Then conduct: see who is working, what needs attention, review code, and merge finished branches. Conductor is built around the idea that developers are becoming AI managers, coordinating many agents at once instead of working through a single chat. It supports Claude Code and Codex, with model selection, Plan Mode, Fast Mode, reasoning controls when available, checkpoints, skills, and agent-specific session controls. Plan Mode asks the agent to make a plan before editing files, making it useful for broad, risky, ambiguous, or multi-file changes. -
22
Claude for Small Business
Anthropic
Claude for Small Business is an AI-powered solution designed to help small businesses automate tasks, streamline workflows, and improve productivity from day one. The platform integrates with widely used business tools like QuickBooks, PayPal, HubSpot, Slack, Canva, Google Workspace, Microsoft 365, and Docusign to centralize operations and simplify daily processes. Claude assists users with tasks such as payroll planning, invoice tracking, financial reconciliation, drafting reminder emails, and creating business forecasts while keeping users involved in important decisions. The platform is built with security in mind and emphasizes that customer data is not used for AI training purposes. Businesses can install the solution quickly without requiring complicated IT setup, making it accessible for growing teams and busy entrepreneurs. Claude also provides tutorials, AI fluency courses, and workflow guidance to help users maximize the benefits of automation and AI tools. -
23
GuardionAI
GuardionAI
GuardionAI is an Agent and MCP Security Gateway that provides unified security for AI agents and Model Context Protocol tools operating on enterprise data. It sits in the execution path to discover, redact sensitive data, enforce protection, and give teams visibility into actions that traditional SIEM, DLP, and identity layers cannot see. Every agent action is inspected, enforced, and logged at the protocol level across AI agents, LLM apps, RAG systems, chatbots, coding agents, MCP servers, internal tools, databases, operating systems, and cloud environments. GuardionAI protects against critical AI threats such as prompt injection, system override, web attacks, MCP tool poisoning, malicious code execution, NSFW content, PII and credential exposure, confidential data leakage, off-topic drift, and unauthorized access, mapped to OWASP LLM Top 10 and agentic AI threat frameworks. Its gateway provides four layers of protection. -
24
Puter.js
Puter.js
Puter.js AI allows developers to integrate artificial intelligence capabilities directly into their applications using models from various providers. It supports tasks such as chat, text-to-image, image-to-text, text-to-video, and text-to-speech conversion, making it possible to build AI-powered apps without managing a separate backend or setting up individual provider keys. Through the chat, developers can chat with AI models, analyze images and videos, and perform function calls using more than 500 models from OpenAI, Anthropic, Google, xAI, Mistral, OpenRouter, DeepSeek, and other providers. The chat API supports options such as model selection, streaming responses, tool calling, image input, video input, and structured interactions, with a default model available when no specific model is selected. Function calling lets AI models request data or perform actions by calling developer-defined functions, enabling applications to access real-time information and more. -
25
SubQ 1.1 Small
Subquadratic
SubQ 1.1 Small is a long-context AI model from Subquadratic designed to reason over complete enterprise artifacts such as codebases, document collections, contracts, and financial filings. It uses Subquadratic Sparse Attention, or SSA, to reduce the high compute costs normally associated with processing very large context windows. The model delivers near-perfect long-context retrieval across 1M, 2M, 6M, and 12M token tests while using far less attention compute than dense attention. SubQ 1.1 Small also maintains strong general reasoning, coding, knowledge, and agentic task performance across multiple benchmarks. Its capabilities make it useful for financial analysis, legal review, contract work, software engineering, due diligence, and other workflows where information is spread across large artifacts. SubQ is built for organizations that want to move beyond fragmented retrieval pipelines and enable direct reasoning over massive bodies of information. -
26
UnoRouter
UnoRouter
UnoRouter is an OpenAI-compatible LLM gateway. One API key gives you 200+ models across providers (OpenAI, Anthropic, Google and more), drop-in for coding agents like Claude Code, Cline, Codex and Kilo Code. Point any OpenAI SDK at the base URL and switch models without changing code. UnoRouter also includes a built-in chat and character client (personas, lorebooks, SillyTavern card import) on the same key. Usage-based pricing with a free tier, live model and price data.Starting Price: Free tier, usage-based -
27
Constellation Gate AI
Constellation Gate AI
Constellation Gate AI is a drop-in defense layer for AI agents, built to sit between the agent and the model while screening every request for attacks and leaks. Gate acts as an inline gateway for coding agents and model APIs, protecting workflows without requiring major code changes. Users can point existing tools such as Claude Code, Cursor, OpenClaw, Codex, or OpenCode at Gate and inherit prompt-injection defense, secret scanning, PII redaction, token optimization, and a verifiable audit trail. The platform is designed around three real risks: prompt injection, credential and PII leakage, and hijacked tool calls. Instead of relying on the model to defend itself, Gate blocks attacks before they reach the model, redacts secrets before responses return, and stops attacker-controlled tool outputs before an agent acts on them. Gate accepts the same calls an agent already makes, forwards them to the model, scans every call and response in both directions. -
28
HQ
Indigo AI
HQ is the shared AI context layer for teams, giving the whole team and every AI tool one workspace to work from, with knowledge, skills, and workflows compounding in one place, and any agent running on top. It works as an operating system for AI workers over Claude Code, Cursor, Codex, ChatGPT, and Claude chat through MCP, so every teammate and every agent can start from the same shared context instead of separate chat histories, scattered files, and siloed workflows. HQ turns one person’s best work into team infrastructure: any prompt or workflow can become a reusable /command, then /hq-sync ships it to the whole team so anyone can run it in one step. Knowledge that usually lives across decisions, docs, playbooks, policies, projects, code, and ideas accumulates in HQ as the team works, creating one source of truth that every agent can search, reuse, and build on. Agents can be deployed into email and Slack, acting on top of the team’s skills and knowledge with full context. -
29
Ming-Flash Omni 2.0
Ant Group
Ming-Flash Omni 2.0 is a full-modal large language model from Ant Group, built on a unified multimodal architecture with “modal unity + task unity” as its core design philosophy. As part of the Ming series, it is designed to achieve cross-modal understanding and generation across text, images, audio, and video, allowing one model to see, hear, speak, and draw instead of relying on multiple specialized models. Ming-Flash Omni 2.0 follows the evolution of Ming-Light Omni and Ming-Flash Omni Preview, moving from unified architecture validation and hundred-billion-parameter scaling to a Data Scaling strategy that achieves open-source SOTA performance on multiple benchmarks. The model integrates four core capability modules: image-text understanding, video analysis, speech synthesis, and image generation or editing. For image-text understanding, Ming introduces structured knowledge graphs for fine-grained visual perception. -
30
Agentcard
Agentcard
Agentcard gives AI agents a safe way to pay for things online by issuing disposable virtual Visa cards built for agent workflows. Instead of sharing a real card in chat or making a human finish checkout, users can create single-use cards with fixed spend limits that self-destruct after one authorized payment. Agentcard is designed around control: a human approves every card and every charge, real card details are never shared with the agent, and users receive notifications when an agent tries to create a card or make a payment. It works with ChatGPT, Claude Desktop, Claude Code, OpenClaw, Cursor, and MCP-compatible agents through one-click integrations, an MCP server, CLI tools, REST API, Chrome Extension, and admin tools for companies. Agents can create cards, check balances, list transactions, close cards, and use cards to complete online purchases while the user stays in control.