# Federated Search

> Use this tool when you need to search across multiple data sources simultaneously, such as knowledge graphs, session history, and web search, to retrieve relevant information. It solves the problem of information fragmentation by providing a unified search surface, allowing AI agents to query diverse data sources with a single request. The tool accepts search queries as input and returns consolidated search results as output.

Canonical page: https://skillsregistry.net/skills/arktechnwa-federated-search  
JSON: https://api.skillsregistry.net/v1/skills/arktechnwa-federated-search

## Description

A federation MCP server that sits in front of multiple memory backends and presents a unified search surface to AI agents, allowing a single query to search across knowledge graphs, session history, and web search.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/z9gn3qriu7)
- **Repository:** <https://github.com/ArkTechNWA/federated-search>

## 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": "arktechnwa-federated-search"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/arktechnwa-federated-search` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/arktechnwa-federated-search/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