skills/agent-memory-mcp/SKILL.md
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
npx skillsauth add legendaryabhi/agent-skills-hub agent-memory-mcpInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
Clone the Repository:
Clone the agentMemory project 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)
memory_searchSearch for memories by query, type, or tags.
query (string), type? (string), tags? (string[])memory_search({ query: "authentication", type: "pattern" })memory_writeRecord new knowledge or decisions.
key (string), type (string), content (string), tags? (string[])memory_write({ key: "auth-v1", type: "decision", content: "..." })memory_readRetrieve specific memory content by key.
key (string)memory_read({ key: "auth-v1" })memory_statsView analytics on memory usage.
memory_stats({})This skill includes a standalone dashboard to visualize memory usage.
npm run start-dashboard <absolute_path_to_target_workspace>
Access at: http://localhost:3333
development
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
development
Implement DeFi protocols with production-ready templates for staking, AMMs, governance, and lending systems. Use when building decentralized finance applications or smart contract protocols.
tools
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
testing
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.