mcpField
B
Build the container

Build the container

Local
github.com/actual-awgCloud & Infra1Updated 77w ago

About Build the container

A Docker-based MCP server for retrieving biological sequence data from NCBI. It is configured to run over stdio with Claude Desktop.

Key features

  1. 01Fetch biological sequence data from NCBI
  2. 02Docker-based build and runtime
  3. 03stdio transport

Use cases

  1. 01Retrieve NCBI sequence data through Claude Desktop
  2. 02Run the server in a Docker container

MCP support

Exposes NCBI biological sequence retrieval to MCP clients. The README describes a Docker-based stdio setup for Claude Desktop.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"ncbi-fetcher": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ncbi-mcp-server"
]
}
}
}
Run commanddocker run -i --rm ncbi-mcp-server

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
ocincbi-mcp-server

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

to get this running you will need to clone the repository and cd into the directory, then run:

Build the container

docker build -t ncbi-mcp-server .

Run with stdio transport (for Claude Desktop)

docker run -it --rm ncbi-mcp-server

make sure you add this to claude_desktop_config.json ($env:AppData\Claude\claude_desktop_config.json on windows)

json{
  "mcpServers": {
    "ncbi-sequence-fetcher": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ncbi-mcp-server"
      ]
    }
  }
}

Comments

Markdown supported

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.