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Today we're also rolling out Model Context Protocol (MCP) inside Deepwork. Proxy already lets anyone automate the web; MCP takes it further - connecting Deepwork to Linear, Asana, Sentry and Intercom, with more integrations coming soon.

195,689 次观看 • 1 年前 •via X (Twitter)

11 条评论

AshutoshShrivastava 的头像
AshutoshShrivastava1 年前

Awesome .. Proxy is more powerful now

MightyBot 的头像
MightyBot1 年前

🧠 Unified Search. Smarter Meetings. Effortless CRM. MightyBot is your AI agent platform for seamless workflows—record meetings, automate CRM updates, and find answers across apps in seconds. 🌟 Focus on what matters. We'll handle the grind.

✧Heavens✧ 的头像
✧Heavens✧1 年前

Let's goooooo!

_k11i_ 的头像
_k11i_1 年前

now we are talking

Just__Irene 的头像
Just__Irene1 年前

This level of integration is exactly what teams need to stay in flow and avoid constant context switching.

♤ 的头像
1 年前

Low-friction improvements like this make tech upgrades painless

SARAH 的头像
SARAH1 年前

Finally, a unified way to manage cross-platform workflows without constant context switching.

Met Ngala : ̗̀➛ 的头像
Met Ngala : ̗̀➛1 年前

This looks incredibly well thought-out.

𝙎𝙃𝙊𝙍𝙀𝙀𝙉 的头像
𝙎𝙃𝙊𝙍𝙀𝙀𝙉1 年前

Huge for fast-moving teams.

AGAFE 的头像
AGAFE1 年前

Real-time context from different tools in one place is exactly what teams need.

🅜🅐🅝🅤 的头像
🅜🅐🅝🅤1 年前

Respecting existing workflows makes adoption easier and less disruptive.

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New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

141,941 次观看 • 1 年前