filesystem vs jiki

Side-by-side comparison to help you pick between these two MCP servers.

	filesystem by modelcontextprotocol	jiki by teilomillet
Stars	★ 85,748	★ 17
30d uses	—	—
Score	77	37
Official	✓	—
Categories	File SystemDeveloper ToolsProductivity	AI / LLM ToolsDeveloper ToolsProductivity
Language	TypeScript	Python
Last commit	this month	13 mo ago

filesystem · Summary

A feature-rich MCP server for filesystem operations with dynamic directory access control.

jiki · Summary

Jiki is a Python framework that connects LLMs to external tools via MCP, offering both orchestration and client capabilities.

filesystem · Use cases

Enable AI models to read and write project files during development
Allow Claude or other MCP clients to browse and analyze codebases
Provide secure sandboxed access to specific directories for content generation

jiki · Use cases

Building tool-augmented LLM applications with calculator or other custom tools
Creating interactive chat interfaces that can call external APIs via MCP
Integrating LLM capabilities with existing systems through standardized protocol

filesystem · Install

Installation

Using NPX

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/directory"
      ]
    }
  }
}

Using Docker

{
  "mcpServers": {
    "filesystem": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--mount", "type=bind,src=/path/to/allowed/dir,dst=/projects/allowed/dir",
        "mcp/filesystem",
        "/projects"
      ]
    }
  }
}

VS Code Extension

Click the installation buttons in the README to install directly in VS Code.

jiki · Install

Installation

Install the jiki package using your preferred package manager:

# Using pip
pip install jiki

# Or using uv (recommended for faster installation)
uv add jiki

Set Up API Key

Jiki uses [LiteLLM](https://litellm.ai/) internally, allowing it to work with a wide range of LLM providers (OpenAI, Anthropic, Gemini, etc.). You need to set the appropriate environment variable for your chosen provider.

# Example for Anthropic Claude (often used as default)
export ANTHROPIC_API_KEY=your_key_here

# Example for OpenAI
# export OPENAI_API_KEY=your_key_here

Comparison generated from public README + GitHub signals. Last updated automatically.