# LODA MCP Server

> Use this tool when you need to efficiently search and retrieve relevant document sections for large language models (LLMs) within specified token budgets. It solves problems of slow document retrieval and excessive token usage by utilizing section-aware parsing and Bloom filter elimination. The LODA MCP Server takes in search queries and token budgets as inputs and returns relevant document sections as outputs, making it ideal for use cases where high-speed and zero-dependency access to large documents is required.

Canonical page: https://skillsregistry.net/skills/patrickkarle-loda-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/patrickkarle-loda-mcp-server

## Description

Provides token-efficient document search and retrieval for LLMs by returning relevant document sections within specified token budgets. It utilizes section-aware parsing and Bloom filter elimination to offer high-speed, zero-dependency access to large documents.

## Trust

- **Trust score (0–1):** 0.86
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/p399g6zw3a)
- **Repository:** <https://github.com/patrickkarle/loda-mcp-server>

## 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": "patrickkarle-loda-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/patrickkarle-loda-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/patrickkarle-loda-mcp-server/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