agent-memory-mcp
A hybrid memory system that allows agents to read, write, and search long-term project knowledge.
Install
mkdir -p .claude/skills/agent-memory-mcp && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/961" && unzip -o skill.zip -d .claude/skills/agent-memory-mcp && rm skill.zipInstalls to .claude/skills/agent-memory-mcp
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).Key capabilities
- →Search memories by query or tags
- →Write new knowledge or decisions
- →Retrieve specific memory content by key
- →View memory usage statistics
How it works
It runs as an MCP server that provides tools to read, write, and search a persistent memory bank. It syncs with project documentation to maintain long-term context.
Inputs & outputs
When to use agent-memory-mcp
- →Storing architectural design patterns
- →Saving project-wide decision logs
- →Retrieving context about existing codebase structures
About this skill
Agent Memory Skill
This skill provides a persistent, searchable memory bank that automatically syncs with project documentation. It runs as an MCP server to allow reading/writing/searching of long-term memories.
Prerequisites
- Node.js (v18+)
Setup
-
Clone the Repository: Clone the
agentMemoryproject into your agent's workspace or a parallel directory:git clone https://github.com/webzler/agentMemory.git .agent/skills/agent-memory -
Install Dependencies:
cd .agent/skills/agent-memory npm install npm run compile -
Start the MCP Server: Use the helper script to activate the memory bank for your current project:
npm run start-server <project_id> <absolute_path_to_target_workspace>Example for current directory:
npm run start-server my-project $(pwd)
Capabilities (MCP Tools)
memory_search
Search for memories by query, type, or tags.
- Args:
query(string),type?(string),tags?(string[]) - Usage: "Find all authentication patterns" ->
memory_search({ query: "authentication", type: "pattern" })
memory_write
Record new knowledge or decisions.
- Args:
key(string),type(string),content(string),tags?(string[]) - Usage: "Save this architecture decision" ->
memory_write({ key: "auth-v1", type: "decision", content: "..." })
memory_read
Retrieve specific memory content by key.
- Args:
key(string) - Usage: "Get the auth design" ->
memory_read({ key: "auth-v1" })
memory_stats
View analytics on memory usage.
- Usage: "Show memory statistics" ->
memory_stats({})
Dashboard
This skill includes a standalone dashboard to visualize memory usage.
npm run start-dashboard <absolute_path_to_target_workspace>
Access at: http://localhost:3333
When not to use it
- →Storing transient session data
- →Replacing primary project documentation
Prerequisites
Limitations
- →Requires manual setup of MCP server
- →Memory retrieval depends on query quality
How it compares
It offers a searchable, persistent memory bank for AI agents instead of relying on standard file-based storage.
Compared to similar skills
agent-memory-mcp side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| agent-memory-mcp (this skill) | 8 | 6mo | Review | Intermediate |
| synap | 0 | 1mo | Review | Intermediate |
| context-management | 1 | 8mo | No flags | Intermediate |
| braindump | 7 | 5mo | No flags | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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