About MCP Servers
MCP Servers is a Python workspace for running a bot and adding MCP server packages. Its README describes a template-based process for including new servers in the workspace and bot.
Key features
- 01Run the bot with `uv run mcpservers`
- 02Install dependencies with `uv sync`
- 03Create servers from a template
- 04Register packages in the uv workspace
Use cases
- 01Run the MCP Servers bot
- 02Start a new server package from the template
MCP support
The project is organized around MCP servers and provides steps to add a server package to the bot. The README does not specify which tools or resources the servers expose.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Servers
Installation
Install uv: instructions
pipx install uv
Install package
uv sync
Usage
Run the bot:
uv run mcpservers
Add New MCP Server
- Copy
servers/templatemcpdirectory toservers/directory and rename it to your server name. - Add you server to
uv.workspace.membersinpyproject.tomlfile.
[tool.uv.workspace]
members = ["servers/templatemcp", "servers/planningmcp", "servers/yourmcp"]
[tool.uv.sources]
templatemcp = { workspace = true }
planningmcp = { workspace = true }
yourmcp = { workspace = true }
- Add your MCP server to bot in
mcpservers.clifile.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.