If by “MCP server” you mean a server implementing the Model Context Protocol (MCP) to allow LLMs / AI agents to interact with external tools/data sources, here are some of the best SDKs & frameworks — trade-offs, strengths & caveats — to help you choose one. If you meant something else by “MCP server,” happy to adjust.

##What is MCP

The Model Context Protocol (MCP) is an open protocol by Anthropic to standardize how large language models (LLMs) can integrate with external tools, data sources, file systems, prompts, etc. (ウィキペディア) There are official SDKs in many languages, reference server implementations, and a growing ecosystem of tools. (Model Context Protocol)

##What to Look for in a Good MCP Server SDK

Before picking one, consider:

##Official SDKs & Languages

Anthropic maintains official SDKs that support server and client building. Languages include:

• TypeScript (Model Context Protocol)
• Python (Model Context Protocol)
• Go (Model Context Protocol)
• Kotlin / Swift / Java / C# / Ruby / Rust / PHP (Model Context Protocol)

These SDKs implement the core MCP protocol features such as:

• Exposing “tools, resources, prompts” via MCP servers. (Model Context Protocol)
• Building MCP clients to connect to servers. (Model Context Protocol)
• Supporting different transports (local, remote) and ensuring protocol compliance. (Model Context Protocol)

So using one of these “official” SDKs is usually the safest bet for compatibility & future support.

##Popular / Recommended Implementations & Servers

Depending on what your MCP server needs to do, some reference / community servers are more mature or better suited. Some examples:

##Pros & Cons

Pros:

• Easy extensibility: you can expose new “tools” or “resources” as MCP endpoints.
• Standardization: once clients & servers follow MCP, tools become interoperable.
• Rapid prototyping: you can spin up servers for local file access, APIs, etc. fairly quickly.

Cons / risks:

• Security risks — giving AI agents access to powerful tools (filesystem, OS commands, network) can be dangerous if permissions are too open. Must sandbox / control carefully.
• Complexity as the number of tools/tools-APIs grows: tool discovery, versioning, schema drift, etc.
• Latency / overhead in some scenarios (esp remote transport).
• Maintenance burden, especially if you build custom servers.

##My Take: Best SDKs

If I were to pick “best” SDKs / approach, here are what I’d recommend depending on scale / team size / urgency:

• For a small team/prototype: Python SDK — very mature, many libraries/tools, quick to experiment.
• For integration into existing large codebases or production, or if you need high performance/type safety: TypeScript / Go. Especially if you have a Node.js or cloud-native stack.
• If your target is mobile / iOS / Android, using Kotlin or Swift SDKs may make sense.

If you tell me your constraints (language(s), deployment environment, what tools you need, security/privacy concerns), I can recommend the best specific MCP SDK + server implementation for your use-case. Do you want me to do that?