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Glama

MCP Memory Server

by keleshteri

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
PROJECT_ROOTYesThe path to your project directory where the MCP memory server will store data and track files

Schema

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Tools

Functions exposed to the LLM to take actions

NameDescription
start_session

Start a new AI coding session with a specific task

add_session_step

Record completion of a step in the current session

add_decision

Record an important technical decision

get_project_memory

Get current project memory and session state

set_file_approval

Set approval status for a file

get_file_approval_status

Get approval status for a file

check_before_modification

Check if a file can be modified according to AI metadata rules

get_modification_actions

Get actions that should be taken after modifying a file

parse_file_metadata

Parse AI metadata from a file

update_file_metadata

Update AI metadata in a file

find_files_with_metadata

Find all files that contain AI metadata

add_changelog_entry

Add an entry to the project changelog

get_file_changelog

Get changelog entries for a specific file

get_recent_changes

Get recent changelog entries

generate_folder_map

Generate or update a _map.md file for a specific folder

generate_all_folder_maps

Generate _map.md files for all folders in the project

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/keleshteri/mcp-memory'

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