# awesome-agentic-knowledge-base

> Use this tool when you need to explore and compare the architectures of popular AI agent repositories, or to inform your own project's design decisions regarding storage, memory, and retrieval systems. It provides a ranked map of 46 trending AI agent repos, detailing their actual implementations and adoption rates. Ideal for developers and researchers seeking empirical insights to optimize their AI agent development workflow.

Canonical page: https://skillsregistry.net/skills/irresi-awesome-agentic-knowledge-base  
JSON: https://api.skillsregistry.net/v1/skills/irresi-awesome-agentic-knowledge-base

## Description

Empirical map of 46 trending AI agent repos: storage, memory, MCP, retrieval — what they actually use, ranked by adoption

## Trust

- **Trust score (0–1):** 0.55
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [GitHub](https://github.com/irresi/awesome-agentic-knowledge-base)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "irresi-awesome-agentic-knowledge-base"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/irresi-awesome-agentic-knowledge-base` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/irresi-awesome-agentic-knowledge-base/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt