List of Ditto Integrations
This is a list of platforms and tools that integrate with Ditto. This list is updated as of July 2026.
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Slack is a workplace collaboration platform that connects teams, tools, data, workflows, and AI agents in one conversational workspace. It is built around channels, where people can organize discussions by project, department, customer, workflow, or business priority. The platform helps teams communicate through messaging, huddles, clips, files, canvases, lists, Slack Connect, and shared workspaces with external partners. Slackbot brings AI into the flow of work by helping users search company knowledge, summarize conversations, prepare for meetings, analyze documents, create briefs, schedule meetings, and take action across connected apps. Slack’s AI features use business context from conversations, files, channels, Salesforce data, and approved integrations while respecting permissions and access controls. Teams can use Slack to work with agents such as Agentforce, Claude, GitHub Copilot, and other connected AI tools. Workflow Builder allows both technical and non-technical users to automate recurring processes such as stand-ups, approvals, reminders, project updates, and operational alerts. Slack’s integration ecosystem connects with apps such as Google Drive, Salesforce, GitHub, Zoom, Asana, Box, Workday, Vercel, ChatGPT, and many others, allowing teams to bring scattered work into one place. Enterprise search helps users find files, decisions, messages, customer records, and historical context without digging through separate systems. Slack also supports secure external collaboration through Slack Connect, making it easier to communicate with customers, vendors, partners, and clients. With AI assistance, real-time communication, workflow automation, enterprise integrations, and secure collaboration, Slack helps organizations reduce silos and run more of their business from a single platform.
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Claude Code
Anthropic
Revolutionize coding with seamless AI assistance and integration.Claude Code is an advanced AI coding assistant created to deeply understand and work within real software projects. Unlike traditional coding tools that focus on syntax or snippets, it comprehends entire repositories, dependencies, and architecture. Developers can interact with Claude Code directly from their terminal, IDE, Slack workspace, or the web interface. By using natural language prompts, users can ask Claude to explain unfamiliar code, refactor components, or implement new features. The tool performs agentic searches across the codebase to gather context automatically, removing the need to manually select files. This makes it especially valuable when joining new projects or working in large, complex repositories. Claude Code can also run CLI commands, tests, and scripts as part of its workflow. It integrates with version control platforms to help manage issues, commits, and pull requests. Teams benefit from faster iteration cycles and reduced context switching. Claude Code supports multiple powerful Claude models depending on the plan selected. Usage scales from short sprints to large, ongoing development efforts. Overall, it acts as a collaborative coding partner that enhances productivity without disrupting established workflows. -
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Model Context Protocol (MCP)
Anthropic
Seamless integration for powerful AI workflows and data management.The Model Context Protocol (MCP) serves as a versatile and open-source framework designed to enhance the interaction between artificial intelligence models and various external data sources. By facilitating the creation of intricate workflows, it allows developers to connect large language models (LLMs) with databases, files, and web services, thereby providing a standardized methodology for AI application development. With its client-server architecture, MCP guarantees smooth integration, and its continually expanding array of integrations simplifies the process of linking to different LLM providers. This protocol is particularly advantageous for developers aiming to construct scalable AI agents while prioritizing robust data security measures. Additionally, MCP's flexibility caters to a wide range of use cases across different industries, making it a valuable tool in the evolving landscape of AI technologies.
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