# Lore MCP Server

> Use this tool when you need to efficiently query a codebase's structural knowledge, such as symbols, imports, and call graphs, to improve the accuracy of LLM agents. It enables agents to access codebase information via MCP, reducing token usage and enhancing correctness. Ideal for use cases where raw file access is impractical or inefficient, the Lore MCP Server provides a streamlined interface for LLM agents to retrieve relevant codebase data.

Canonical page: https://skillsregistry.net/skills/jafreck-lore  
JSON: https://api.skillsregistry.net/v1/skills/jafreck-lore

## Description

Enables LLM agents to query a codebase's structural knowledge (symbols, imports, call graphs, etc.) via MCP, reducing tokens and improving correctness compared to raw file access.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mba6yinn9e)
- **Repository:** <https://github.com/jafreck/Lore>

## 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": "jafreck-lore"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jafreck-lore` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jafreck-lore/pull`

---
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