Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
list_memory_sectionsA

List all available memory sections. Use this to discover what project context is stored. Returns section names and descriptions.

read_memoryA

Read a memory section. Use this to retrieve stored project context such as architecture decisions, API contracts, conventions, bugs, todos, or glossary. Prefer reading memory before scanning unrelated source files.

write_memoryA

Overwrite a memory section with new content. WARNING: This replaces the entire section. Use with care. Prefer append_decision or append_api_contract for adding entries. Only use write_memory when you need to restructure or rewrite a full section.

append_decisionA

Record an architecture or design decision. Use this after making a significant technical choice. Stores a structured ADR (Architecture Decision Record) with context, decision, consequences, and related files. Do not store full source code — store only the rationale and outcome.

append_api_contractA

Use this tool after creating or modifying an API endpoint. Store only the durable endpoint contract: method, path, auth, request shape, response shape, side effects, frontend usage, and related files. Do not store full source code.

search_memoryA

Use this tool before scanning the codebase when the user asks about project architecture, API contracts, decisions, bugs, conventions, or previous implementation choices. Searches all memory sections using keyword matching and returns matching lines with surrounding context.

summarize_memoryA

Get a compact overview of project memory. Returns headings and short excerpts for each section. Use this for a quick orientation before diving into specific sections with read_memory.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Latest Blog Posts

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/gregoire-renaldo/memory-mcp'

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