MemRL: MCP Server for Self-Evolving Agents via Reinforcement Learning on Episodic Memory
Setup
Choose your client, copy the config, then fill in any required environment variables.
claude mcp add tempera -- npx -y @astudioplus/tempera-mcp~/.codex/config.toml
[mcp_servers.tempera]
command = "npx"
args = ["-y", "@astudioplus/tempera-mcp"]
# codex mcp add tempera -- npx -y @astudioplus/tempera-mcp~/.cursor/mcp.json
{
"mcpServers": {
"tempera": {
"command": "npx",
"args": [
"-y",
"@astudioplus/tempera-mcp"
]
}
}
}.vscode/mcp.json
{
"servers": {
"tempera": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@astudioplus/tempera-mcp"
]
}
}
}~/.gemini/settings.json
{
"mcpServers": {
"tempera": {
"command": "npx",
"args": [
"-y",
"@astudioplus/tempera-mcp"
]
}
}
}claude_desktop_config.json
{
"mcpServers": {
"tempera": {
"command": "npx",
"args": [
"-y",
"@astudioplus/tempera-mcp"
]
}
}
}.trae/mcp.json
{
"mcpServers": {
"tempera": {
"command": "npx",
"args": [
"-y",
"@astudioplus/tempera-mcp"
]
}
}
}