File System MCP Server

An MCP (Model Context Protocol) server that exposes filesystem operations — listing directories, reading, writing, and searching files — as tools an LLM can discover and invoke at runtime. Built as a learning project to understand MCP's architecture from the ground up, using the low-level Server API (raw JSON Schemas, not the decorator-based FastMCP shortcut).

What this project demonstrates

• How an MCP server advertises capabilities to a host via tools/list, and how the host routes an LLM's tool-call decision back via tools/call

• Why tool descriptions are prompt engineering, not documentation — the LLM only ever sees the JSON Schema, never your source code

• Defensive server design: path sandboxing, input validation, structured error responses instead of crashes, and result truncation for large outputs

• The read-only vs. destructive vs. idempotent distinction MCP tool annotations are meant to capture

Related MCP server: MCP Server

Architecture

Host (Claude Desktop / MCP Inspector / any MCP client)
   │
   │  tools/list  →  server responds with schemas for all 4 tools
   │  tools/call  →  host sends {name, arguments}, server executes and
   │                 returns a result
   ▼
This server (stdio transport)
   │
   ▼
sandbox/  (all file operations are confined to this directory)

The server never calls the LLM and the LLM never calls the server directly — the host sits in between, using the schemas below to decide when and how to invoke each tool.

Tools

All tools operate relative to a sandboxed root directory (./sandbox) — paths are resolved and verified to stay inside that boundary before any filesystem access happens, blocking path-traversal attempts like ../../etc/passwd.

Setup

uv sync

Running

With the MCP Inspector (recommended for development — shows raw protocol traffic and lets you call tools manually):

npx @modelcontextprotocol/inspector uv run main.py

Open the URL it prints, click Connect, then Tools → List Tools to see all four schemas, and run any tool directly from the form UI.

As a server for an MCP host (e.g. Claude Desktop), add to your host's MCP config:

{
  "mcpServers": {
    "fs-mcp-server": {
      "command": "uv",
      "args": ["run", "--directory", "/absolute/path/to/fs-mcp-server", "main.py"]
    }
  }
}

Security design

• Sandboxing (resolve_safe_path): every incoming path is joined onto the sandbox root, resolved to an absolute path, and checked with Path.is_relative_to() to confirm it didn't escape via .. segments. Rejected paths raise a caught ValueError, never crash the server.

• Overwrite protection: write_file will not silently clobber an existing file — it requires an explicit overwrite: true argument.

• Result truncation: search_files caps output at 100 matches and notes when results were truncated, rather than risking an enormous response.

• Graceful failure everywhere: missing arguments, non-existent paths, wrong path types (file vs. directory), and unreadable/binary files all return a structured error message to the caller instead of raising an uncaught exception.

Known limitations / next steps

• Tool annotations (readOnlyHint, destructiveHint, idempotentHint) are not yet set explicitly — without them, hosts may apply incorrect defaults (e.g. flagging a read-only tool as destructive).

• Currently stdio transport only; could be extended to streamable HTTP for remote deployment.

• search_files content search reads full file contents into memory per candidate file — fine for a learning project, would need streaming for very large files in production.

Stack

Python, mcp (official Anthropic SDK), uv for dependency management.