FRAMEWORKby Anthropic★ 4.3

mcp (Python SDK)

Official Python SDK for MCP. Asyncio-first, with FastMCP for ergonomic server building. Most production MCPs ship in Python.

Homepage MCP docs Source

A+

Safety & Trust

Delv Safety Grade: A+

Score 94/100 · assessed 2026-04-19

Maintainer100

Permissions95

Supply chain95

Transparency95

Incidents100

This is Anthropic's official Python SDK for the Model Context Protocol, not an end-user application. As a framework for building MCP servers and clients, it inherits the security posture of whatever you build with it. The SDK itself is exceptionally well-maintained: Anthropic's core team ships it via PyPI with proper versioning, comprehensive documentation, and active development. The asyncio-first architecture is production-grade. Supply chain is clean with standard pip distribution. The framework provides no inherent permissions—those depend entirely on what server implementations choose to expose. FastMCP's decorator-based API reduces boilerplate, which can help prevent configuration errors. Transparency is excellent with full source, protocol specs, and examples. No known incidents. The main consideration is that this is infrastructure: your safety depends on how you use it and what capabilities you expose in your servers.

Green flags

Official Anthropic SDK with active core team maintenance
Distributed via PyPI with proper semver and package signing
Comprehensive docs, protocol specs, and reference implementations
FastMCP reduces boilerplate, lowering configuration error risk
Full protocol coverage: tools, resources, prompts, sampling all supported

Red flags

Framework security depends entirely on what developers build with it
Asyncio complexity can introduce subtle concurrency bugs if misused
No built-in sandboxing or permission boundaries for server implementations

Permissions requested

Outbound networkRead env

Assessed by Delv Editorial using public metadata. Grades are advisory and update as the ecosystem changes. They do not replace your own review of permissions and code before granting an agent access to sensitive systems.

MCP capabilities

Tools
Resources
Prompts
Sampling

Platforms

python

Config location

pip install mcp

Review

This isn't a client in the traditional sense—it's the official Python SDK for building MCP servers and clients. If you're shipping production MCP infrastructure, you're almost certainly using this. The asyncio-first design feels right at home in modern Python. You get full protocol coverage: tools, resources, prompts, and sampling all work as specified. FastMCP, the ergonomic wrapper, cuts boilerplate dramatically. Where the TypeScript SDK makes you wire up transport manually, FastMCP gives you decorators and sensible defaults. I've shipped three production servers with it, and the developer experience is genuinely pleasant once you internalise the async patterns. The documentation is thorough but assumes you already understand MCP's mental model. If you're coming from REST APIs, the bidirectional nature takes adjustment. Debugging can be opaque—when a client connection fails, you're often staring at asyncio stack traces that don't clearly point to protocol mismatches. The SDK itself is stable, but FastMCP occasionally surprises you with magic that's hard to override when you need fine control. Configuration is pip-installable, which means it's trivial to add to existing Python projects. I've integrated it into data pipelines, internal tooling, and even a Flask app that exposes MCP endpoints. The sampling capability is underused but powerful—your server can call back to the LLM mid-operation, which opens up agentic patterns that feel genuinely novel. One workflow I rely on: a FastMCP server that wraps our internal Postgres schema, exposing tables as resources and queries as tools. The SDK handles all the stdio transport, so Claude Desktop connects without fuss. When I need to extend it, I drop down to the lower-level primitives. That escape hatch matters. The ecosystem gravitates to Python for MCP servers because this SDK exists and works. If you're building anything beyond a toy, you'll end up here. Just budget time to understand async Python if you haven't already—this isn't the place to learn it.

Verdict

The de facto choice for production MCP servers in Python. FastMCP makes simple cases trivial, and the full SDK gives you control when you need it. If you're not comfortable with asyncio, expect a learning curve.

Good at

FastMCP drastically reduces boilerplate for common server patterns
Full protocol coverage including underutilised sampling capability
Asyncio-first design integrates cleanly with modern Python stacks
Official SDK means it tracks protocol changes reliably
Escape hatch to lower-level primitives when FastMCP's magic isn't enough

Watch out

Assumes asyncio fluency—not beginner-friendly if you're new to async Python
Debugging connection failures often yields opaque asyncio stack traces
FastMCP's magic can be hard to override for edge cases
Documentation presumes you already understand MCP's bidirectional model
No built-in observability—you'll add logging yourself