mcp_espn_ff vs memory
Side-by-side comparison to help you pick between these two MCP servers.
mcp_espn_ff by KBThree13 | memory by modelcontextprotocol | |
|---|---|---|
| Stars | ★ 30 | ★ 85,748 |
| 30d uses | — | — |
| Score | 40 | 77 |
| Official | — | ✓ |
| Categories | AI / LLM ToolssportsOther | Knowledge GraphAI / LLM ToolsProductivity |
| Language | Python | TypeScript |
| Last commit | 5 mo ago | this month |
mcp_espn_ff · Summary
ESPN Fantasy Football MCP server providing league data, team rosters, and player stats through tools.
memory · Summary
An MCP server implementing persistent memory using a local knowledge graph for AI models to remember user information across chats.
mcp_espn_ff · Use cases
- Ask an AI assistant about your fantasy football team's performance and player stats
- Get matchup information and league standings through natural language queries
- Manage your fantasy football roster using voice commands to an AI assistant
memory · Use cases
- Personalizing AI assistant interactions by remembering user preferences, history, and relationships
- Building context-aware chat applications that maintain conversation history
- Creating knowledge bases that persist across AI model sessions
mcp_espn_ff · Install
Installation
Prerequisites
- Python 3.10 or higher
uvpackage manager- Claude Desktop for the best experience
Usage with Claude Desktop
- Update the Claude Desktop config:
- MacOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Include reference to the MCP server:
```json { "mcpServers": { "espn-fantasy-football": { "command": "uv", "args": [ "--directory", "/absolute/path/to/directory", "run", "espn_fantasy_server.py" ] } } }
- Restart Claude Desktop
memory · Install
Installation
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}VS Code
Use one-click installation buttons or manually configure in .vscode/mcp.json:
{
"servers": {
"memory": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}Docker
{
"mcpServers": {
"memory": {
"command": "docker",
"args": ["run", "-i", "-v", "claude-memory:/app/dist", "--rm", "mcp/memory"]
}
}
}