typescript-sdk VS servers

Model Context Protocol Documentation - Complete MCP reference Typescript SDK

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For TypeScript you can refer to https://github.com/modelcontextprotocol/typescript-sdk/blob/...

There isn't much documentation available right now but you can ask coding agent eg. Claude Code to generate an example.

@modelcontextprotocol/sdk: MCP server framework

At the time of this writing, this is little more than a proof of concept as a combination of the starter Pulsar package-generator package, the Atom package creation tutorial and the example from the official MCP Typescript SDK with some editor tool functions registered. Hopefully it will become more soon, since I am looking forward to actually using it to build stuff!

MCP TypeScript SDK

For this, we're going to use McpServer from the modelcontextprotocol SDK. The SDK supports: Resources, Tools, Prompts. However for this demo we'll only need tools.

Building a custom MCP server is straightforward with the right tools. While servers can be written in any language supporting stdout, official SDKs simplify the process. The TypeScript SDK is a great starting point.

For me it was implementing a simple `execute_terminal_command` tool along with hooking up to my company's jira and gitlab (dont worry security gurus, for the command line, I have a hardcoded list of allowed read-only commands that the LLM can execute, and both jira and gitlab servers likewise have readonly options.

What I will say is I agree there should be an option to get rid of the chat confirmations of every single new tool call in a chat - as well as building a set of "profiles" of different tools depending what I'm working on. Also strongly agree there needs to be an internal prompt possibility to explicitely tell the LLM what tool(s) to favor and how to use them (even in addition to the descriptions / schemas of the tools themselves) I opened an issue on the anthropic repo exactly about this: https://github.com/modelcontextprotocol/typescript-sdk/issue...

AI agents have become integral to modern development workflows, transforming how we build and maintain software. While these tools are already powerful, they reach their full potential when enhanced with MCP (Model Context Protocol) servers that extend their capabilities through specialized tools and integrations.

MCP Server Lists: modelcontextprotocol/servers

AI agents are transforming how we work, but they're often limited by their training data. MCP (Model Context Protocol) servers bridge this gap by giving AI agents access to real-time data, external APIs, and custom tools.

GitHub MCP

Option 2: Community MCP Servers Several community-maintained servers are available in the MCP servers repository.

Official MCP servers - GitHub repo includes filesystem, GitHub, GitLab, Slack, and Google Drive implementations

The Figma MCP server provides programmatic access to Figma files through a standardized interface. Unlike the REST API, MCP provides structured access optimized for AI context.

Model Context Protocol Specification

MCP (Model Context Protocol) is an open protocol that enables AI assistants like Claude to interact with external tools and data sources. It's basically a standardized way for AI to use your APIs. You can read more in the official docs.