MCP Memory Server

Describes the environment variables required to run the server.

Name	Required	Description	Default
`PROJECT_ROOT`	Yes	The path to your project directory where the MCP memory server will store data and track files

Server capabilities have not been inspected yet.

Functions exposed to the LLM to take actions

Name	Description
start_sessionC	Start a new AI coding session with a specific task
add_session_stepC	Record completion of a step in the current session
add_decisionC	Record an important technical decision
get_project_memoryB	Get current project memory and session state
set_file_approvalC	Set approval status for a file
get_file_approval_statusC	Get approval status for a file
check_before_modificationC	Check if a file can be modified according to AI metadata rules
get_modification_actionsC	Get actions that should be taken after modifying a file
parse_file_metadataC	Parse AI metadata from a file
update_file_metadataC	Update AI metadata in a file
find_files_with_metadataC	Find all files that contain AI metadata
add_changelog_entryC	Add an entry to the project changelog
get_file_changelogC	Get changelog entries for a specific file
get_recent_changesC	Get recent changelog entries
generate_folder_mapC	Generate or update a _map.md file for a specific folder
generate_all_folder_mapsB	Generate _map.md files for all folders in the project
update_last_editorC	Update @last-editor field in a file with Git author information
update_all_last_editorsB	Update @last-editor fields in all files with Git author information
get_file_last_editorC	Get the last editor of a file from Git history

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

Latest Blog Posts

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'

If you have feedback or need assistance with the MCP directory API, please join our Discord server